Claude Code MCP
The Claude Code MCP server enables AI-powered software engineering tasks through a standardized Model Context Protocol interface, providing various tools for code analysis, file operations, and system interactions including:
Execute shell commands with security restrictions using the
bashtoolRead and edit files using
readFileandeditFiletoolsList and search files with
listFiles,searchGlob, andgreptoolsAnalyze and review code using the
codeReviewtoolThink through complex problems using the
thinktoolAccess file contents, directory listings, and system environment information as resources
Utilize predefined prompts for tasks like CLI interaction, code review, PR review, and codebase initialization
Provides capabilities for code review and project exploration, which likely involves Git integration
Server can be run using Node.js and provides environment information including Node.js version
Provides environment information including npm version
Implements tools for executing shell commands with security restrictions
Implementation uses TypeScript with full type safety
Uses Zod schemas for MCP tool argument validation
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Claude Code MCPreview this Python function for security issues"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Claude Code MCP
Claude Code MCP is an implementation of Claude Code as a Model Context Protocol (MCP) server. This project allows you to use Claude Code's powerful software engineering capabilities through the standardized MCP interface.
⚠️ DISCLAIMER ⚠️
Claude Code MCP is a auto-generated project by DevinAI, who was prompted to analyse the Claude Code codebase, and generate an MCP server.
This is a proof of concept that I don't advise anyone to use.
What is Claude Code?
Claude Code is Anthropic's CLI tool for software engineering tasks, powered by Claude. It provides a set of tools and capabilities that help developers with:
Code generation and editing
Code review and analysis
Debugging and troubleshooting
File system operations
Shell command execution
Project exploration and understanding
The original implementation is available as a JavaScript module that defines prompts and tools for interacting with Claude's API.
Related MCP server: MCP Tool
What is MCP?
The Model Context Protocol (MCP) is a standardized interface for AI models that enables consistent interaction patterns across different models and providers. MCP defines:
Tools: Functions that models can call to perform actions
Resources: External data that models can access
Prompts: Predefined conversation templates
By implementing Claude Code as an MCP server, we make its capabilities available to any MCP-compatible client, allowing for greater interoperability and flexibility.
Features
Full implementation of Claude Code functionality as an MCP server
Provides tools for file operations, shell commands, and code analysis
Exposes resources for accessing file system and environment information
Includes prompts for general CLI interaction and code review
Compatible with any MCP client
TypeScript implementation with full type safety
Installation
# Clone the repository
git clone https://github.com/auchenberg/claude-code-mcp.git
cd claude-code-mcp
# Install dependencies
npm install
# Build the project
npm run buildUsage
Running as a standalone server
# Start the server
npm startUsing with MCP clients
Claude Code MCP can be used with any MCP client. Here's an example of how to connect to it using the MCP TypeScript SDK:
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
const transport = new StdioClientTransport({
command: "node",
args: ["dist/index.js"]
});
const client = new Client(
{
name: "example-client",
version: "1.0.0"
},
{
capabilities: {
prompts: {},
resources: {},
tools: {}
}
}
);
await client.connect(transport);
// Use Claude Code through MCP
const result = await client.callTool({
name: "bash",
arguments: {
command: "ls -la"
}
});
console.log(result);Available Tools
Claude Code MCP provides the following tools:
bash: Execute shell commands with security restrictions and timeout options
readFile: Read files from the filesystem with options for line offsets and limits
listFiles: List files and directories with detailed metadata
searchGlob: Search for files matching a glob pattern
grep: Search for text in files with regex pattern support
think: A no-op tool for thinking through complex problems
codeReview: Analyze and review code for bugs, security issues, and best practices
editFile: Create or edit files with specified content
Tool Details
bash
{
command: string; // The shell command to execute
timeout?: number; // Optional timeout in milliseconds (max 600000)
}The bash tool includes security restrictions that prevent execution of potentially dangerous commands like curl, wget, and others.
readFile
{
file_path: string; // The absolute path to the file to read
offset?: number; // The line number to start reading from
limit?: number; // The number of lines to read
}searchGlob
{
pattern: string; // The glob pattern to match files against
path?: string; // The directory to search in (defaults to current working directory)
}grep
{
pattern: string; // The regular expression pattern to search for
path?: string; // The directory to search in (defaults to current working directory)
include?: string; // File pattern to include in the search (e.g. "*.js", "*.{ts,tsx}")
}Available Resources
file: Access file contents (
file://{path})Provides direct access to file contents with proper error handling
Returns the full text content of the specified file
directory: List directory contents (
dir://{path})Returns a JSON array of file information objects
Each object includes name, path, isDirectory, size, and modified date
environment: Get system environment information (
env://info)Returns information about the system environment
Includes Node.js version, npm version, OS info, and environment variables
Available Prompts
generalCLI: General CLI prompt for Claude Code
Provides a comprehensive system prompt for Claude to act as a CLI tool
Includes guidelines for tone, style, proactiveness, and following conventions
Automatically includes environment details
codeReview: Prompt for reviewing code
Specialized prompt for code review tasks
Analyzes code for bugs, security vulnerabilities, performance issues, and best practices
prReview: Prompt for reviewing pull requests
Specialized prompt for PR review tasks
Analyzes PR changes and provides comprehensive feedback
initCodebase: Initialize a new CLAUDE.md file with codebase documentation
Creates documentation for build/lint/test commands and code style guidelines
Useful for setting up a new project with Claude Code
Development
# Run in development mode with auto-reload
npm run devArchitecture
Claude Code MCP is built with a modular architecture:
claude-code-mcp/
├── src/
│ ├── server/
│ │ ├── claude-code-server.ts # Main server setup
│ │ ├── tools.ts # Tool implementations
│ │ ├── prompts.ts # Prompt definitions
│ │ └── resources.ts # Resource implementations
│ ├── utils/
│ │ ├── bash.ts # Shell command utilities
│ │ └── file.ts # File system utilities
│ └── index.ts # Entry point
├── package.json
├── tsconfig.json
└── README.mdThe implementation follows these key principles:
Modularity: Each component (tools, prompts, resources) is implemented in a separate module
Type Safety: Full TypeScript type definitions for all components
Error Handling: Comprehensive error handling for all operations
Security: Security restrictions for potentially dangerous operations
Implementation Details
MCP Server Setup
The main server is set up in claude-code-server.ts:
export async function setupClaudeCodeServer(server: McpServer): Promise<void> {
// Set up Claude Code tools
setupTools(server);
// Set up Claude Code prompts
setupPrompts(server);
// Set up Claude Code resources
setupResources(server);
}Tool Implementation
Tools are implemented using the MCP SDK's tool registration method:
server.tool(
"toolName",
"Tool description",
{
// Zod schema for tool arguments
param1: z.string().describe("Parameter description"),
param2: z.number().optional().describe("Optional parameter description")
},
async ({ param1, param2 }) => {
// Tool implementation
return {
content: [{ type: "text", text: "Result" }]
};
}
);Resource Implementation
Resources are implemented using the MCP SDK's resource registration method:
server.resource(
"resourceName",
new ResourceTemplate("resource://{variable}", { list: undefined }),
async (uri, variables) => {
// Resource implementation
return {
contents: [{
uri: uri.href,
text: "Resource content"
}]
};
}
);License
MIT
Acknowledgements
Claude Code by Anthropic
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Disclaimer
This project is not officially affiliated with Anthropic. Claude Code is a product of Anthropic, and this project is an independent implementation of Claude Code as an MCP server.
Available Tools
8 toolsbashC
Execute a shell command
| Name | Required | Description | Default |
|---|---|---|---|
| command | Yes | The shell command to execute | |
| timeout | No | Optional timeout in milliseconds (max 600000) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'Execute a shell command' implies a potentially powerful and risky operation, but the description doesn't mention security implications, permission requirements, side effects, or what happens on timeout. This is a significant gap for a tool that can perform arbitrary system operations.
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 extremely concise at just three words, with zero wasted language. It's front-loaded with the essential purpose and doesn't include any unnecessary elaboration, making it efficient for quick understanding.
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 tool that executes arbitrary shell commands with no annotations and no output schema, the description is inadequate. It doesn't address the significant behavioral complexity, security implications, or what the tool returns. Given the power and risk of this operation, more context is needed for safe and effective use.
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?
The schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description doesn't add any additional meaning beyond what's in the schema - it doesn't explain command syntax, shell environment, or timeout behavior. This meets the baseline for high schema coverage.
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 'Execute a shell command' clearly states the verb ('execute') and resource ('shell command'), making the purpose immediately understandable. However, it doesn't distinguish this tool from potential sibling tools that might also execute commands or interact with the shell environment, keeping it from a perfect score.
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 provides no guidance on when to use this tool versus alternatives like 'editFile' or 'listFiles'. There's no mention of prerequisites, safety considerations, or typical use cases, leaving the agent with minimal context for appropriate tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
codeReviewC
Review code for bugs, security issues, and best practices
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | The code to review |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool reviews code but doesn't describe how it operates (e.g., static analysis, AI-based review), what permissions or resources it requires, or the format of results. This leaves significant gaps in understanding the tool's 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 a single, efficient sentence that directly states the tool's purpose without waste. It's appropriately sized for a simple tool, though it could be slightly more structured (e.g., by listing review aspects in bullet points) for better 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 tool's complexity (code review can involve nuanced analysis), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the review outputs (e.g., a list of issues, a summary), how comprehensive it is, or any limitations, making it inadequate for full contextual understanding.
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?
The input schema has 100% description coverage, with the 'code' parameter fully documented in the schema. The description adds no additional meaning beyond the schema, such as code language support or review depth, so it meets the baseline score of 3 for high schema coverage.
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's purpose with specific verbs ('review code') and resources ('bugs, security issues, and best practices'), making it easy to understand what the tool does. However, it doesn't differentiate from potential sibling tools like 'think' or 'bash' that might also analyze code, preventing a perfect score.
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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for code review, or compare it to sibling tools like 'think' for analysis or 'bash' for execution, leaving the agent with minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
editFileC
Create or edit a file
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes | The absolute path to the file to edit | |
| content | Yes | The new content for the file |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the operation without behavioral details. It doesn't disclose whether this overwrites existing files, requires specific permissions, handles errors, or has side effects like creating directories. The vague 'create or edit' leaves critical behavior ambiguous.
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 extremely concise with just three words, front-loaded and zero waste. Every word earns its place by conveying the core action and resource efficiently.
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 mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavior, error handling, or output format, leaving significant gaps for an agent to use it correctly in context with 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?
Schema description coverage is 100%, so the schema fully documents both parameters ('file_path' and 'content'). The description adds no additional meaning beyond implying these parameters are used for the operation, meeting the baseline for high schema coverage.
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's purpose with specific verbs ('create or edit') and resource ('a file'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'readFile' or 'listFiles' beyond the basic operation type.
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 about when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., file permissions), when editing is preferred over creating, or how it relates to siblings like 'readFile' for viewing or 'bash' for file operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
grepC
Search for text in files
| Name | Required | Description | Default |
|---|---|---|---|
| pattern | Yes | The regular expression pattern to search for in file contents | |
| path | No | The directory to search in. Defaults to the current working directory. | |
| include | No | File pattern to include in the search (e.g. "*.js", "*.{ts,tsx}") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'Search for text in files' implies a read-only operation, but it doesn't specify whether this is safe, if it requires permissions, how it handles errors, or what the output format looks like. For a tool with three parameters and no annotations, this is a significant gap in behavioral context.
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, efficient sentence with zero waste—'Search for text in files' is front-loaded and perfectly concise. Every word earns its place by directly conveying the core functionality without unnecessary elaboration.
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 complexity (3 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what the tool returns (e.g., matches, line numbers, file names), how results are formatted, or any behavioral nuances like case sensitivity or recursion. For a search tool, this leaves critical gaps for an AI agent to use it effectively.
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?
The description adds no parameter-specific information beyond what's already in the schema, which has 100% coverage with clear descriptions for 'pattern', 'path', and 'include'. According to the rules, when schema description coverage is high (>80%), the baseline is 3 even with no param info in the description, which applies here.
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 'Search for text in files' clearly states the verb (search) and resource (text in files), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'searchGlob' or 'listFiles' that might also involve searching or file operations, so it doesn't reach the highest level of sibling differentiation.
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 provides no guidance on when to use this tool versus alternatives like 'searchGlob' or 'listFiles'. There's no mention of prerequisites, context, or exclusions, leaving the agent to infer usage based solely on the tool name and basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
listFilesC
Lists files and directories in a given path
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | The absolute path to the directory to list |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the basic action but doesn't describe key behaviors like whether it returns recursive listings, handles symbolic links, includes hidden files, or what happens if the path is invalid. This leaves significant gaps for an agent to understand how the tool behaves beyond the simple listing.
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, clear sentence that directly states the tool's function without any unnecessary words. It's front-loaded with the core action and resource, making it highly efficient and easy to parse.
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 annotations and output schema, the description is incomplete for a tool that performs file system operations. It doesn't address important contextual aspects like error handling, output format, or behavioral details (e.g., recursion, hidden files), which are crucial for an agent to use this tool effectively in real scenarios.
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?
The input schema has 100% description coverage, with the 'path' parameter clearly documented as 'The absolute path to the directory to list'. The description adds no additional semantic information beyond what the schema provides, so it meets the baseline for adequate but unenhanced parameter documentation.
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 ('Lists') and the target ('files and directories in a given path'), making the purpose immediately understandable. However, it doesn't distinguish this tool from potential siblings like 'searchGlob' or 'grep' that might also involve file operations, so it doesn't achieve full differentiation.
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 provides no guidance on when to use this tool versus alternatives like 'searchGlob' or 'grep'. It lacks any context about prerequisites, such as whether the path must exist or be accessible, or when other tools might be more appropriate for similar tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
readFileC
Read a file from the local filesystem
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes | The absolute path to the file to read | |
| offset | No | The line number to start reading from | |
| limit | No | The number of lines to read |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the basic action but lacks details on error handling (e.g., for missing files), performance considerations, or output format (e.g., text vs. binary). This leaves significant gaps in understanding how the tool behaves in practice.
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, direct sentence with no wasted words, making it highly efficient and easy to parse. It front-loads the core purpose without unnecessary elaboration, which is ideal for quick understanding.
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 complexity (file I/O with parameters) and lack of annotations and output schema, the description is insufficient. It doesn't cover critical aspects like return values, error cases, or security implications, leaving the agent poorly equipped to use the tool effectively in real scenarios.
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?
The schema description coverage is 100%, with clear descriptions for all parameters (file_path, offset, limit). The description doesn't add any semantic details beyond what the schema provides, such as explaining how offset and limit interact or file encoding issues. This meets the baseline for high schema coverage.
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 ('Read') and resource ('a file from the local filesystem'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'grep' or 'searchGlob' that also involve file reading operations, which prevents a perfect score.
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 provides no guidance on when to use this tool versus alternatives like 'grep' for searching or 'listFiles' for directory contents. There's no mention of prerequisites, such as file existence or permissions, which leaves the agent without context for appropriate tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
searchGlobC
Search for files matching a pattern
| Name | Required | Description | Default |
|---|---|---|---|
| pattern | Yes | The glob pattern to match files against | |
| path | No | The directory to search in. Defaults to the current working directory. |
TDQS
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. It states the tool searches for files but doesn't describe how it behaves—e.g., whether it returns full paths, file contents, or metadata; if it's recursive or case-sensitive; or any performance or permission considerations. This leaves significant gaps for an agent to understand the tool's 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 a single, efficient sentence that directly states the tool's purpose without any fluff or redundancy. It is appropriately sized and front-loaded, making it easy for an agent to quickly grasp the core functionality.
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 complexity of a file search tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a list of file paths or details), how errors are handled, or any behavioral nuances. This makes it inadequate for an agent to fully understand the tool's context and usage.
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?
The input schema has 100% description coverage, with clear documentation for both parameters ('pattern' and 'path'). The description adds no additional meaning beyond the schema, such as examples of glob patterns or path constraints. Since the schema does the heavy lifting, the 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 'Search for files matching a pattern' clearly states the verb ('search') and resource ('files'), specifying the action and target. However, it doesn't distinguish this tool from sibling tools like 'grep' or 'listFiles', which might offer similar file-searching capabilities, so it lacks sibling differentiation.
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 provides no guidance on when to use this tool versus alternatives. It doesn't mention when to prefer 'searchGlob' over 'grep' for pattern matching or 'listFiles' for file listing, nor does it specify any prerequisites or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
thinkC
A tool for thinking through complex problems
| Name | Required | Description | Default |
|---|---|---|---|
| thought | Yes | Your thoughts |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the tool is for 'thinking through complex problems,' without disclosing behavioral traits like whether it's read-only, has side effects, requires authentication, or produces output. This leaves significant gaps in understanding how the tool behaves.
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, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized for a simple tool, though it could be more front-loaded with specific details to 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 tool's conceptual nature, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'thinking through' results in, how the tool aids problem-solving, or what the agent should expect, leaving too much ambiguity for effective use.
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?
The schema description coverage is 100%, with the single parameter 'thought' described as 'Your thoughts.' The description adds no additional meaning beyond this, so it meets the baseline of 3 where the schema handles the parameter documentation adequately.
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 'A tool for thinking through complex problems' states a general purpose but lacks specificity about what 'thinking through' entails or what resource it operates on. It distinguishes from siblings like 'bash' or 'readFile' by being about cognitive processing rather than file operations, but remains vague about the actual function.
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 is provided. The description implies usage for complex problems, but it doesn't specify contexts, prerequisites, or exclusions, leaving the agent to infer based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
8 tool updates
- First observed
bash - First observed
codeReview - First observed
editFile - First observed
grep - First observed
listFiles - First observed
readFile - First observed
searchGlob - First observed
think
TDQS
Most tools have distinct purposes, such as bash for shell execution, codeReview for analysis, and file operations like editFile, readFile, and listFiles. However, grep and searchGlob could be slightly confusing as both involve searching, though grep targets text content while searchGlob focuses on file patterns, which is clarified in descriptions.
The naming is mixed with camelCase (codeReview, editFile, readFile, listFiles, searchGlob) and lowercase (bash, grep, think), lacking a uniform pattern. While the camelCase tools follow a verbNoun style, the inconsistency in case usage reduces predictability across the set.
With 8 tools, the count is well-scoped for a code and file management server, covering essential operations like execution, review, file handling, and search. Each tool serves a clear purpose without feeling excessive or insufficient for the domain.
The toolset provides strong coverage for code and file workflows, including creation, reading, editing, listing, searching, and review. A minor gap is the lack of a deleteFile tool, which agents might need to work around, but core operations are well-represented.
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