Open Context is a high-performance MCP server that fetches and caches up-to-date documentation from official sources for programming languages, frameworks, and tools, making it instantly available to AI assistants like Claude, Cursor, and Claude Code.
Search & Browse Documentation
Search across all topics with optional language filtering (open-context_search_docs)
Get detailed docs for a specific topic by ID, name, or language (open-context_get_docs)
List all available documentation languages and topics (open-context_list_docs)
Language & Framework Coverage (15 specialized tools)
Go: versions and package docs from pkg.go.dev
JavaScript/TypeScript: npm packages, Node.js, TypeScript, React, and Next.js versions
Python: package metadata and docs from PyPI
Rust: crate information from crates.io
DevOps/Infrastructure: Ansible, Terraform, Jenkins, Kubernetes, and Helm versions (via GitHub releases)
Docker: Hub image info including tags and details
GitHub Actions: metadata, inputs, and outputs from the GitHub API
Key Features
Smart caching: Configurable TTL (default 7 days) for fast repeated queries and offline use; manually clear cache to force fresh fetches
Flexible deployment: stdio mode for local MCP clients or HTTP mode for remote access with health checks and SSE support
Custom documentation: Extend the knowledge base with local documentation files for any language or framework
Fetches documentation and crate information for the Actix Rust framework via crates.io.
Provides documentation and version information for Ansible.
Retrieves package metadata and documentation for the Django framework via PyPI integration.
Fetches details and documentation for images hosted on Docker Hub.
Retrieves metadata and documentation for the Express.js framework via the npm registry.
Provides documentation and package information for the Gin web framework from official Go sources.
Fetches documentation and metadata for GitHub Actions.
Provides documentation and version information for Helm.
Fetches package metadata and documentation for JavaScript libraries through npm integration.
Retrieves documentation for Jenkins versions and automation topics.
Provides documentation and version information for Kubernetes.
Fetches documentation and version details for the Next.js framework.
Retrieves Node.js version information and official documentation.
Fetches package metadata and installation instructions from the npm registry.
Retrieves package metadata and documentation for the NumPy library via PyPI integration.
Fetches metadata and documentation for Python packages from the Python Package Index.
Retrieves package metadata and documentation for Python libraries.
Provides documentation and version information for the React library.
Fetches documentation and crate information for Rust libraries from crates.io.
Provides documentation and version information for Terraform.
Fetches documentation and version details for TypeScript.
A high-performance MCP (Model Context Protocol) server that provides up-to-date documentation for programming languages, frameworks, and tools. Built in Go for speed and simplicity.
Open Context fetches and caches documentation from official sources, making it instantly available to AI assistants like Claude. Instead of relying on outdated training data, get real-time access to:
Go: Standard library docs, third-party packages, version release notes
JavaScript/TypeScript: npm packages, Node.js, React, Next.js versions
Python: PyPI packages with installation instructions and package metadata
Rust: Crates.io packages with version info and documentation links
DevOps Tools: Docker, Kubernetes, Helm, Terraform, Ansible, Jenkins, GitHub Actions
And more: Easy to extend with any language or framework
Related MCP server: devdocs-mcp
Always Up-to-Date: Fetches from official sources (pkg.go.dev, npm registry, PyPI, crates.io, GitHub releases, GitHub API, Docker Hub)
Smart Caching: Local cache with configurable TTL (default: 7 days)
Fast & Lightweight: Written in Go, starts in milliseconds
Two Transport Modes: stdio for local use, HTTP for remote servers
MCP Native: Seamless integration with Claude Desktop, Cursor, and Claude Code
Using Homebrew (macOS/Linux):
brew tap incu6us/homebrew-tap
brew install open-contextUsing the install script:
curl -fsSL https://raw.githubusercontent.com/incu6us/open-context/master/install.sh | bashOr build from source:
git clone https://github.com/incu6us/open-context
cd open-context
go build -o open-contextPrerequisites for building: Go 1.25 or higher
Choose your client and follow the setup instructions:
Find your config file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Add open-context:
{
"mcpServers": {
"open-context": {
"command": "/path/to/open-context"
}
}
}Restart Claude Desktop
Go to Settings > Tools & Integrations > MCP Servers
Add this configuration:
{
"open-context": {
"command": "/path/to/open-context"
}
}Restart Cursor
Option A: Local binary (stdio transport)
claude-code mcp add open-context /path/to/open-contextOption B: Remote server (HTTP transport)
Start the server on your remote machine:
./open-context --transport http --host 0.0.0.0 --port 9011Install via Claude CLI:
claude mcp add --transport http open-context http://your-server.com:9011In your conversation with Claude, just type:
use open-context for goor
create dockerfile using latest alpine image. use open-contextClaude will automatically fetch and use the documentation to answer your questions!
brew tap incu6us/homebrew-tap
brew install open-contextThe installation script automates everything:
curl -fsSL https://raw.githubusercontent.com/incu6us/open-context/master/install.sh | bash# Clone repository
git clone https://github.com/incu6us/open-context
cd open-context
# Option 1: Build manually
go build -o open-context
# Option 2: Use make
make build
# Or: make setup (builds + shows next steps)go install github.com/incu6us/open-context@latestThe binary will be in $GOPATH/bin/open-context (usually ~/go/bin/open-context).
Open Context creates a config file at ~/.open-context/config.yaml on first run.
# How long to keep cached documentation
# Formats: "7d" (days), "24h" (hours), "30m" (minutes), "0" (never expire)
cache_ttl: 7dExample configurations:
Offline work: cache_ttl: 0 (never expires)
Daily updates: cache_ttl: 24h
Weekly updates: cache_ttl: 7d (default)
# Use your preferred editor
nano ~/.open-context/config.yaml
code ~/.open-context/config.yaml
vim ~/.open-context/config.yamlChanges take effect on next server start.
stdio transport (default) - For local MCP clients:
./open-contextHTTP transport - For remote access or HTTP-based clients:
# Default (localhost:9011)
./open-context --transport http
# Custom host and port
./open-context --transport http --host 0.0.0.0 --port 3000
# Short flags
./open-context -t http -H 0.0.0.0 -p 9011HTTP endpoints:
GET /health - Health check
POST /message - MCP JSON-RPC messages
GET /sse - Server-Sent Events stream
# Clear cache (full flag)
./open-context --clear-cache
# Clear cache (short alias)
./open-context --ccThis removes ~/.open-context/cache/. Data will be refetched on next use.
# Show help
./open-context --help
# Show version
./open-context --versionOnce configured, activate documentation in your conversation:
use open-context for go
use open-context for typescript
use open-contextClaude will automatically:
Discover available documentation
Use the appropriate tools
Fetch information from official sources
Cache results locally
Go package documentation:
What's new in Go 1.21?
Show me how to use github.com/gin-gonic/ginnpm packages:
Get the latest version of express
Show me React 18 featuresDevOps tools:
What's in Kubernetes 1.28?
Show me Terraform 1.6 changes
Get the golang:1.25-alpine Docker image detailsSee USING_PROMPTS.md for more examples.
The server provides 15 MCP tools for fetching documentation:
Tool | Description |
| Search across all documentation |
| Get specific documentation topic |
| List all available documentation |
Tool | What it Fetches | Example |
| Go versions & packages | Go 1.21, github.com/gin-gonic/gin |
| npm packages | express, react |
| Python packages (PyPI) | requests, django, numpy |
| Rust crates (crates.io) | serde, tokio, actix-web |
| Node.js versions | 20.0.0, 18.17.0 |
| TypeScript versions | 5.0.0, 4.9.5 |
| React versions | 18.0.0, 17.0.2 |
| Next.js versions | 14.0.0, 13.5.0 |
| Ansible versions | 2.15.0 |
| Terraform versions | 1.6.0 |
| Jenkins versions | 2.420 |
| Kubernetes versions | 1.28.0 |
| Helm versions | 3.13.0 |
| Docker Hub images | golang:1.25-alpine |
| GitHub Actions | actions/checkout, docker/setup-buildx-action |
All tools automatically:
Fetch from official sources
Cache results locally
Return markdown-formatted documentation
Include installation/usage examples
For detailed tool documentation, see the Tools Reference below.
You can add custom documentation for any language or framework.
1. Create directory structure:
mkdir -p data/jenkins/topics2. Create metadata file (data/jenkins/metadata.json):
{
"name": "jenkins",
"displayName": "Jenkins",
"description": "Jenkins CI/CD automation documentation"
}3. Add documentation topics (data/jenkins/topics/pipeline-basics.json):
{
"id": "pipeline-basics",
"title": "Jenkins Pipeline Basics",
"description": "Introduction to Jenkins declarative pipelines",
"keywords": ["pipeline", "jenkinsfile", "ci", "cd"],
"content": "# Jenkins Pipeline Basics\n\n[Your markdown content here]"
}4. Restart the server
See data/README.md for complete documentation format guide.
Run tests:
# Quick automated test
./test.sh
# Unit tests
go test ./...
# With race detector
go test -race ./...Add a new MCP tool:
Add tool definition in server/server.go → handleToolsList()
Implement handler in server/server.go → handleToolCall()
Add provider method in docs/provider.go (if needed)
Project structure:
open-context/
├── main.go # Entry point & CLI
├── server/
│ ├── server.go # MCP protocol & tool handlers
│ └── http.go # HTTP transport
├── docs/
│ └── provider.go # Documentation search & retrieval
├── fetcher/ # External source fetchers
│ ├── go_fetcher.go
│ ├── npm_fetcher.go
│ └── ...
├── cache/ # Cache management
└── data/ # Local documentation storageSearch for documentation topics across all languages.
Parameters:
query (required): Search query
language (optional): Filter by language (e.g., "go", "typescript")
Example:
Search for "goroutines" in Go documentationGet detailed documentation for a specific topic.
Parameters:
id (optional): Topic ID from search results
language (optional): Programming language
topic (optional): Topic name (alternative to ID)
Example:
Get documentation for topic "basics" in GoList all available documentation languages and topics.
Example:
List all available documentationFetch Go version information or package documentation.
Parameters:
type (required): "version" or "library"
version (conditional): Go version (e.g., "1.21") for versions, or library version
importPath (conditional): Import path (e.g., "github.com/gin-gonic/gin") for libraries
Examples:
Get information about Go version 1.21
Get information about github.com/gin-gonic/gin
Get information about github.com/spf13/cobra version v1.8.0Sources:
Versions: go.dev release notes
Libraries: pkg.go.dev package documentation
See GO_VERSION_LIBRARY_FEATURE.md for details.
Fetch npm package information.
Parameters:
packageName (required): Package name (e.g., "express", "react")
Source: npm registry
Fetch Python package information from PyPI.
Parameters:
packageName (required): Package name (e.g., "requests", "django", "numpy")
version (optional): Specific version (defaults to latest)
Source: PyPI (Python Package Index)
Fetch Rust crate information from crates.io.
Parameters:
crateName (required): Crate name (e.g., "serde", "tokio", "actix-web")
version (optional): Specific version (defaults to latest)
Source: crates.io
Fetch Node.js version information.
Parameters:
version (required): Node.js version (e.g., "20.0.0")
Source: GitHub releases
Fetch TypeScript version information.
Parameters:
version (required): TypeScript version (e.g., "5.0.0")
Source: GitHub releases
Fetch React version information.
Parameters:
version (required): React version (e.g., "18.0.0")
Source: GitHub releases
Fetch Next.js version information.
Parameters:
version (required): Next.js version (e.g., "14.0.0")
Source: GitHub releases
Fetch Ansible version information.
Parameters:
version (required): Ansible version (e.g., "2.15.0")
Source: GitHub releases
Fetch Terraform version information.
Parameters:
version (required): Terraform version (e.g., "1.6.0")
Source: GitHub releases
Fetch Jenkins version information.
Parameters:
version (required): Jenkins version (e.g., "2.420")
Source: GitHub releases
Fetch Kubernetes version information.
Parameters:
version (required): Kubernetes version (e.g., "1.28.0")
Source: GitHub releases
Fetch Helm version information.
Parameters:
version (required): Helm version (e.g., "3.13.0")
Source: GitHub releases
Fetch Docker image information from Docker Hub.
Parameters:
image (required): Image name (e.g., "golang", "nginx", "myuser/myapp")
tag (required): Image tag (e.g., "1.25-alpine", "latest")
Example:
Get Docker image golang:1.25-alpineSource: Docker Hub API
Fetch GitHub Action information from GitHub API.
Parameters:
repository (required): GitHub repository in format "owner/repo" (e.g., "actions/checkout", "docker/setup-buildx-action")
version (optional): Specific version/tag of the action (defaults to latest release)
Example:
Get GitHub Action actions/checkout
Get GitHub Action docker/setup-buildx-action with version v2.10.0Source: GitHub API
Go package fetching from pkg.go.dev
HTTP transport for remote servers
Version fetchers for major tools
Python packages (PyPI)
Rust crates (crates.io)
Version-specific documentation
Web UI for browsing docs
Contributions welcome! Areas where you can help:
Add new language/framework fetchers
Improve documentation
Add test coverage
Report bugs or suggest features
Share your use cases
See TESTING.md for comprehensive testing guide.
MIT License - see LICENSE file for details.
Inspired by context7 by Upstash.
Questions? Open an issue on GitHub
Fetch and cache information about Ansible versions from GitHub releases
| Name | Required | Description | Default |
|---|---|---|---|
| version | Yes | Ansible version to fetch (e.g., '2.15.0', '2.16.0') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. It mentions 'cache', which is a behavioral trait, but does not elaborate on caching details (e.g., TTL, refresh). For a read-only operation, this is adequate but could be more transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that directly conveys the tool's purpose without extraneous information. Every word is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter, no output schema, and read-only behavior, the description sufficiently covers purpose and data source. No additional context is necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema fully documents the 'version' parameter. The description adds the context of caching but no additional parameter semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetch and cache information') and the resource ('Ansible versions from GitHub releases'). The name and sibling tools differentiate it from other technology-specific tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus siblings or when not to. The context of sibling names implies use for Ansible, but no direct alternatives or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and cache information about Docker images from Docker Hub, including available tags and image details
| Name | Required | Description | Default |
|---|---|---|---|
| tag | Yes | Docker image tag (e.g., '1.23.4-bookworm', 'latest', '20-alpine') | |
| image | Yes | Docker image name (e.g., 'golang', 'node', 'nginx', 'myuser/myapp') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry full burden. It mentions 'cache information' which hints at caching behavior but does not disclose rate limits, authentication needs, or error handling. The phrase 'including available tags and image details' gives some clarity on return content.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no redundant information. Every word contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately conveys the tool returns 'information about Docker images... including available tags and image details'. This provides sufficient context for a simple lookup tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with both 'image' and 'tag' parameters clearly described. The description adds 'including available tags and image details' but does not substantially augment the schema beyond baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Fetch and cache information about Docker images from Docker Hub', specifying the verb 'Fetch and cache' and the resource 'Docker images'. It distinguishes itself from siblings which are about different technologies like Ansible, Kubernetes, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for Docker image info but does not explicitly state when to use this tool vs alternatives. No guidance on when not to use or prerequisite conditions is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get detailed documentation for a specific topic or library
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Documentation topic ID (from search results) | |
| topic | No | Topic name (alternative to ID) | |
| language | No | Documentation name (e.g., 'go', 'typescript') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description is too brief (one sentence) and does not mention any behavioral traits such as read-only nature, side effects, authentication requirements, or return behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at one sentence, but it omits critical details for effective use. Conciseness should not come at the expense of completeness; a few more sentences would improve clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and annotations, and the presence of many sibling tools, the description should explain what 'detailed documentation' includes and how the output is structured. The current description is insufficient for an agent to fully understand the tool's capabilities.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each parameter having a brief description. However, the tool description adds no additional meaning beyond what the schema provides, such as clarifying the relationship between 'id' and 'topic' or the expected format of 'language'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Get detailed documentation for a specific topic or library', which clearly indicates the purpose is retrieving documentation. However, it does not differentiate this generic tool from sibling tools that target specific technologies (e.g., get_go_info, get_python_info), which also provide documentation-like info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus the many sibling tools that focus on specific technologies. The description does not mention that for language-specific documentation, the dedicated tools should be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and cache information about GitHub Actions from GitHub API, including action metadata, inputs, and outputs
| Name | Required | Description | Default |
|---|---|---|---|
| version | No | Specific version/tag of the action (optional, defaults to latest release) | |
| repository | Yes | GitHub repository in format 'owner/repo' (e.g., 'actions/checkout', 'docker/setup-buildx-action') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses caching behavior and that it fetches from GitHub API, but it does not mention other behavioral traits such as authentication requirements, rate limits, or side effects. The disclosure is partial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence of 18 words that covers the core purpose. There is no redundancy or unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple fetch tool with two parameters and no output schema, the description provides adequate context about the resource and what is returned. It could mention the need for network access or API authentication, but overall it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters. The description adds value by mentioning what the data includes (metadata, inputs, outputs), but does not significantly augment parameter meaning beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the resource (GitHub Actions) and the action (fetch and cache information), listing what is included (metadata, inputs, outputs). It distinguishes itself from sibling tools which target different technologies (e.g., Ansible, Docker).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when GitHub Action info is needed, but it does not explicitly state when to use this tool versus alternatives or provide any exclusions. The sibling tools are domain-specific, so context is clear, but no explicit guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and cache information about specific Go versions or Go libraries from official sources
| Name | Required | Description | Default |
|---|---|---|---|
| type | Yes | Type of information to fetch: 'version' for Go release info or 'library' for Go package/library info | |
| version | No | Go version to fetch (e.g., '1.21', '1.22') when type is 'version', or library version when type is 'library' | |
| importPath | No | Import path of the Go library (e.g., 'github.com/gin-gonic/gin') when type is 'library' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Mentions caching behavior, but lacks disclosure on authentication, rate limits, or other traits, with no annotations to compensate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single concise sentence with front-loaded purpose, no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate but does not describe the output format or what information is returned, given no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so description adds no extra meaning beyond the schema's parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description specifies fetching and caching info about Go versions or libraries, clearly distinguishing from siblings focused on other technologies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implicitly for Go-related queries, but no explicit when-to-use or alternatives are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and cache information about Helm versions from GitHub releases
| Name | Required | Description | Default |
|---|---|---|---|
| version | Yes | Helm version to fetch (e.g., '3.12.0', '3.13.0') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions caching, which indicates a performance trait. However, it does not disclose what information is returned, any side effects, or whether the operation is read-only. The description adds some value beyond the schema but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It efficiently conveys the basic purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema, no annotations), the description is minimally adequate. However, it could be improved by specifying what information is returned or any constraints on the version format. It does not cover all potentially useful details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% because the only parameter 'version' has a clear description with examples. The tool description does not add any extra semantics beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Fetch and cache') and resource ('Helm versions from GitHub releases'), clearly distinguishing it from sibling tools like open-context_get_ansible_info or open-context_get_kubernetes_info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives. It only states the purpose, leaving the agent to infer usage context. Given the many similar siblings, explicit guidance is needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and cache information about Jenkins versions from GitHub releases
| Name | Required | Description | Default |
|---|---|---|---|
| version | Yes | Jenkins version to fetch (e.g., '2.440.3', '2.450.0') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the burden. It discloses caching behavior but lacks details on error handling, rate limits, or data format. For a simple fetch tool, it is adequate but could be more transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys the essential information without any fluff. It is front-loaded and efficiently communicates the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one parameter, no output schema), the description is largely complete. It covers what the tool does and the source. Missing details about the output format are a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing a clear example of the version parameter. The description adds 'from GitHub releases', giving source context beyond the schema, which is useful for the agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it fetches and caches information about Jenkins versions from GitHub releases. The verb 'fetch and cache' and resource 'information about Jenkins versions' are specific, and the naming distinguishes it from sibling tools that target other technologies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for Jenkins version information but does not explicitly state when to use it versus alternatives, nor does it provide exclusions. The context is clear from the tool name, but no when-not or alternative guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and cache information about Kubernetes versions from GitHub releases
| Name | Required | Description | Default |
|---|---|---|---|
| version | Yes | Kubernetes version to fetch (e.g., '1.28.0', '1.29.0') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description mentions 'cache', a behavioral trait. However, it does not disclose read-only nature, authentication needs, rate limits, or other side effects, leaving gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It efficiently conveys the core action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, and the description does not specify what information is returned (e.g., version list, release notes). For a fetch tool, this is a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description adds no extra meaning beyond the parameter name and example. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'fetch and cache', the resource 'Kubernetes versions', and the source 'from GitHub releases'. This distinguishes it from sibling tools which target other technologies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternative sibling tools. The description only states what the tool does, without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and cache information about Next.js versions from GitHub releases
| Name | Required | Description | Default |
|---|---|---|---|
| version | Yes | Next.js version to fetch (e.g., '13.0.0', '14.0.0') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden. It mentions caching but does not disclose safety (read-only), auth needs, rate limits, or behavior on missing versions. Adequate but not transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, 12 words, no wasted words. Concise while conveying purpose, though could include a bit more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description omits what the tool returns (e.g., release data, download links). Caching behavior is mentioned but not elaborated. Adequate for simple tool but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3. The description adds no extra meaning beyond the schema's param description, which already specifies the version format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it fetches and caches information about Next.js versions from GitHub releases, using specific verb+resource and distinguishing from siblings like get_go_info, get_python_info, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives. While the naming implies it's for Next.js version info, given many similar get_*_info tools, some direction would be helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and cache information about Node.js versions from nodejs.org
| Name | Required | Description | Default |
|---|---|---|---|
| version | Yes | Node.js version to fetch (e.g., '18.17.0', 'v20.0.0') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions caching, which is a behavioral trait beyond the schema. However, without annotations, it does not disclose other behaviors like authentication needs, rate limits, or whether the fetch is read-only. The caching disclosure is a positive but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that conveys the tool's purpose without unnecessary words. It is concise and front-loaded, though it could optionally include more detail without harming conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and only minimal context from the description, the tool definition lacks details about the return format or what 'information' encompasses. It is adequate for a simple fetch tool but could provide more context for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'version', and the description does not add additional meaning beyond what the schema already provides. Baseline 3 is appropriate as the description adds no extra context for the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetch and cache'), the resource ('information about Node.js versions'), and the source ('from nodejs.org'). It distinguishes itself from siblings, which are other technology-specific info tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The name and description imply it's for Node.js version info, but there is no mention of when to use or not use it, or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and cache information about npm packages from the npm registry
| Name | Required | Description | Default |
|---|---|---|---|
| version | No | Specific version of the package (optional, defaults to latest) | |
| packageName | Yes | Name of the npm package (e.g., 'express', 'react', '@types/node') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions caching ('Fetch and cache'), which indicates a behavioral trait beyond a simple fetch. However, it does not explain caching details (e.g., duration, storage), network requirements, rate limits, or authentication needs. No annotations are provided to cover these aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words. It is front-loaded with the main action. While very brief, it covers the core purpose without extraneous details. Could benefit from slight expansion for completeness, but conciseness is strong.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description should clarify what information is returned. It only states 'information about npm packages' without specifying the structure or content (e.g., version, dependencies, metadata). Given the complexity of npm package info, this is a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with both parameters having descriptions. The tool description adds the concept of caching but does not provide additional parameter-level semantics beyond what is already in the schema. Baseline score of 3 is appropriate as schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Fetch and cache information about npm packages from the npm registry' uses a specific verb (Fetch and cache) and specifies the resource (npm packages from npm registry). It clearly distinguishes from siblings focused on other ecosystems (e.g., Docker, Ansible).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives. However, the intended use is implied by the tool name and sibling context, as it is clearly for npm packages while siblings cover other ecosystems. No explicit when-not-to-use or alternative naming is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and cache information about Python packages from PyPI (Python Package Index)
| Name | Required | Description | Default |
|---|---|---|---|
| version | No | Specific version of the package (optional, defaults to latest) | |
| packageName | Yes | Name of the Python package (e.g., 'requests', 'django', 'numpy') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions caching behavior, which is a useful trait, but it does not disclose other important aspects like authentication requirements, rate limits, the nature of the returned data (e.g., version, dependencies), or potential side effects. The description is too vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It efficiently communicates the tool's action and source.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description should explain what information is returned (e.g., version, dependencies, metadata). It only says 'information about Python packages,' which is too vague. The tool has two parameters and no output schema, so the description leaves significant ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% because both parameters have clear descriptions in the schema. The description adds no extra meaning beyond the schema; it repeats the source (PyPI). Baseline 3 is appropriate as the schema already documents parameters well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches and caches information about Python packages from PyPI. It uses a specific verb ('Fetch and cache') and resource ('Python packages from PyPI'), and the sibling tools are for different ecosystems, so it is well-distinguished.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives, such as when to use get_python_info vs other ecosystem tools. The context from sibling names implies it is for Python packages, but no exclusions or when-not-to-use instructions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and cache information about React versions from GitHub releases
| Name | Required | Description | Default |
|---|---|---|---|
| version | Yes | React version to fetch (e.g., '18.0.0', '19.0.0') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses caching behavior, which is beyond the input schema. However, without annotations, the description does not mention whether the operation is read-only, destructive, or any rate limits. The caching info adds some value but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no unnecessary words. Front-loaded with action and resource. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool (one parameter, no output schema), the description is mostly complete: it states the action (fetch and cache), source (GitHub releases), and target (React versions). It does not explain the return format but that is acceptable without an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the parameter is fully described in the schema. The description adds no additional meaning beyond stating it fetches the version, which is already in the schema's parameter description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool fetches and caches React version info from GitHub releases. It is specific about the resource (React) and action (fetch and cache), distinguishing it from sibling tools that operate on other technologies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like open-context_get_docs or search_docs. The description does not provide exclusions or context for selection among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and cache information about Rust crates from crates.io
| Name | Required | Description | Default |
|---|---|---|---|
| version | No | Specific version of the crate (optional, defaults to latest) | |
| crateName | Yes | Name of the Rust crate (e.g., 'serde', 'tokio', 'actix-web') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses caching behavior, which is useful, but fails to mention potential side effects like API rate limits, authentication requirements, or error handling for network failures.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: one sentence that is front-loaded with the key action. Every word carries meaning, and there is no unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two well-documented parameters and no output schema, the description provides sufficient context. It explains the data source and caching, though it could be slightly more complete by mentioning return format or error expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so both parameters have descriptions. The description adds minimal semantic value beyond the schema, such as indicating the tool fetches from crates.io. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches and caches information about Rust crates from crates.io. The verb 'Fetch and cache' is specific, and the resource 'Rust crates' differentiates it from sibling tools for other ecosystems.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The sibling list and naming convention imply it is for Rust crates, but the description does not state when-not to use it or mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and cache information about Terraform versions from GitHub releases
| Name | Required | Description | Default |
|---|---|---|---|
| version | Yes | Terraform version to fetch (e.g., '1.5.0', '1.6.0') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions 'fetch and cache' but does not explain caching duration, rate limits, error behavior, or whether network access is required. Significant gaps for an agent to use correctly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with action and resource. No unnecessary words. Efficient communication.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Missing output schema or description of return value. Agent does not know what info is cached/returned (list of versions, release notes, etc.). Also lacks details on caching behavior. Needs more context for a fetch operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%; the parameter 'version' is well-documented. The tool description adds the 'from GitHub releases' context, but this is already implicit. Minimal added value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Fetch and cache' and the resource 'Terraform versions from GitHub releases'. It distinguishes from siblings like open-context_get_ansible_info by focusing on Terraform.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives. The name implies it's for Terraform version info, but there is no mention of prerequisites or exclusions. Sibling tools for other technologies suggest context, but the description lacks direct advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch and cache information about TypeScript versions from GitHub releases
| Name | Required | Description | Default |
|---|---|---|---|
| version | Yes | TypeScript version to fetch (e.g., '5.0.0', '4.9.5') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It mentions caching but lacks details on cache behavior, rate limits, return format, or side effects. The description is too minimal for a safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. However, it could be slightly more structured (e.g., separating fetch and caching aspects).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (one parameter, no output schema), the description is adequate but incomplete. It does not describe the return value or caching details, which are important for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no extra meaning beyond what the schema already provides for the 'version' parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Fetch and cache') and the resource ('information about TypeScript versions from GitHub releases'). It is distinct from sibling tools focused on other technologies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the tool name and sibling context (different technologies), but there is no explicit guidance on when to use this vs alternatives, nor when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all available documentation languages and their topics
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes a read-only operation without mentioning side effects, rate limits, or response format. Adequate for a simple list but minimal behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with clear action, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple (no params, no output schema). Description completely conveys the purpose and scope relative to siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist (schema coverage 100%), so per guidelines baseline is 4. Description does not need to add parameter info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists available documentation languages and their topics, distinguishing it from sibling tools like 'get_docs' (fetches specific docs) and 'search_docs' (searches).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for discovering doc languages and topics, but does not explicitly state when to use it vs alternatives or provide exclusions. No guidance for when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search for documentation topics across all available documentation sources
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query for documentation topics | |
| language | No | Filter by documentation name (e.g., 'go', 'typescript') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as pagination, rate limits, or what documentation sources are searched. The agent lacks critical behavioral insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that conveys the core functionality without redundancy. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool, the description is adequate but lacks information about scope, supported sources, or result format. Without an output schema, more context would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with clear descriptions for both parameters. The description adds no new meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches documentation topics across all sources. However, it does not differentiate from sibling tools like 'list_docs' or 'get_docs', which could have overlapping purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternative search or retrieval tools. No conditions or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.1.1open-context_get_ansible_infoopen-context_get_docker_imageopen-context_get_docsopen-context_get_github_actionopen-context_get_go_infoopen-context_get_helm_infoopen-context_get_jenkins_infoopen-context_get_kubernetes_infoopen-context_get_nextjs_infoopen-context_get_node_infoopen-context_get_npm_infoopen-context_get_python_infoopen-context_get_react_infoopen-context_get_rust_infoopen-context_get_terraform_infoopen-context_get_typescript_infoopen-context_list_docsopen-context_search_docsv1.3.3open-context_get_ansible_infoopen-context_get_docker_imageopen-context_get_docsopen-context_get_github_actionopen-context_get_go_infoopen-context_get_helm_infoopen-context_get_jenkins_infoopen-context_get_kubernetes_infoopen-context_get_nextjs_infoopen-context_get_node_infoopen-context_get_npm_infoopen-context_get_python_infoopen-context_get_react_infoopen-context_get_rust_infoopen-context_get_terraform_infoopen-context_get_typescript_infoopen-context_list_docsopen-context_search_docsv1.1.0open-context_get_ansible_infoopen-context_get_docker_imageopen-context_get_docsopen-context_get_github_actionopen-context_get_go_infoopen-context_get_helm_infoopen-context_get_jenkins_infoopen-context_get_kubernetes_infoopen-context_get_nextjs_infoopen-context_get_node_infoopen-context_get_npm_infoopen-context_get_python_infoopen-context_get_react_infoopen-context_get_rust_infoopen-context_get_terraform_infoopen-context_get_typescript_infoopen-context_list_docsopen-context_search_docsv0.1.2open-context_get_ansible_infoopen-context_get_docker_imageopen-context_get_docsopen-context_get_github_actionopen-context_get_go_infoopen-context_get_helm_infoopen-context_get_jenkins_infoopen-context_get_kubernetes_infoopen-context_get_nextjs_infoopen-context_get_node_infoopen-context_get_npm_infoopen-context_get_python_infoopen-context_get_react_infoopen-context_get_rust_infoopen-context_get_terraform_infoopen-context_get_typescript_infoopen-context_list_docsopen-context_search_docsEach tool targets a distinct technology or documentation function, with no overlap. Info fetchers for different technologies are clearly separated, and documentation tools have unique purposes.
All tools follow a consistent verb_noun snake_case pattern with the server prefix, e.g., 'open-context_get_ansible_info' and 'open-context_list_docs'. There is no mixing of styles.
18 tools is slightly high but still reasonable for a server covering many technologies and documentation. Each tool serves a clear purpose without unnecessary duplication.
The tool set covers fetching info on a wide array of popular technologies and provides documentation retrieval features. Minor gaps exist (e.g., missing Java/Maven), but core functionality is well-covered.
MCP server for accessing curated awesome list documentation
MCP server for opencode documentation, generated by doc2mcp.
MCP server for developer documentation, generated by doc2mcp.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/incu6us/open-context'
If you have feedback or need assistance with the MCP directory API, please join our Discord server
