prisma-cloud-docs-mcp-server
The Prisma Cloud Docs MCP Server provides comprehensive search and indexing capabilities for Prisma Cloud's official documentation and API references via an MCP-compatible client.
Key capabilities:
Index documentation (
index_prisma_docs,index_prisma_api_docs) - Index official Prisma Cloud documentation and API references with configurable page limitsSearch documentation (
search_prisma_docs,search_prisma_api_docs) - Search indexed documentation for specific queriesUnified search (
search_all_docs) - Search across all indexed Prisma Cloud documentation sites simultaneouslyMonitor indexing (
get_index_status) - Check indexing status and view cache statistics
Provides search access to Prisma Cloud documentation and API references, enabling AI agents to query and retrieve information from Prisma Cloud's official documentation sites
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., "@prisma-cloud-docs-mcp-serverhow do I set up cloud account integration in Prisma Cloud?"
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.
Prisma Cloud Docs MCP Server
A Model Context Protocol (MCP) server that provides search access to Prisma Cloud documentation. This server allows Claude and other MCP-compatible clients to search through Prisma Cloud's official documentation and API references.
Note: This server has been migrated to HTTP transport and container deployment for improved scalability and performance. The server now runs in HTTP mode when deployed via Smithery.
Features
Search across Prisma Cloud documentation
Search Prisma Cloud API documentation
Caching system for improved performance
Real-time indexing of documentation sites
Related MCP server: s2-streamstore
Installation
Option 1: From PyPI (Recommended)
No installation needed! Just use uvx in your Claude Desktop configuration.
Installing via Smithery
To install prisma-cloud-docs-mcp-server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @clarkemn/prisma-cloud-docs-mcp-server --client claudeOption 2: Development Installation
Prerequisites
Python 3.12 or higher
uv package manager
Install uv
curl -LsSf https://astral.sh/uv/install.sh | shClone and Setup
git clone https://github.com/clarkemn/prisma-cloud-docs-mcp-server.git
cd prisma-cloud-docs-mcp-server
uv syncUsage
With Claude Desktop
Add this server to your Claude Desktop configuration file:
Location: ~/Library/Application Support/Claude/claude_desktop_config.json (macOS)
Option 1: Direct from PyPI (Recommended)
{
"mcpServers": {
"Prisma Cloud Docs": {
"command": "uvx",
"args": ["prisma-cloud-docs-mcp-server@latest"],
"env": {},
"transport": "stdio"
}
}
}Option 2: Local Development
{
"mcpServers": {
"Prisma Cloud Docs": {
"command": "uv",
"args": ["run", "python", "server.py"],
"cwd": "/path/to/prisma-cloud-docs-mcp-server",
"env": {},
"transport": "stdio"
}
}
}Replace /path/to/prisma-cloud-docs-mcp-server with the actual path to where you cloned this repository.
Manual Testing
You can test the server manually:
echo '{"jsonrpc": "2.0", "id": 1, "method": "initialize", "params": {"protocolVersion": "2024-11-05", "capabilities": {}, "clientInfo": {"name": "test", "version": "1.0"}}}' | uv run python server.pyAvailable Tools
The server provides these MCP tools:
index_prisma_docs(max_pages: int = 50)- Index Prisma Cloud documentation (call this first)index_prisma_api_docs(max_pages: int = 50)- Index Prisma Cloud API documentationsearch_prisma_docs(query: str)- Search Prisma Cloud documentationsearch_prisma_api_docs(query: str)- Search Prisma Cloud API documentationsearch_all_docs(query: str)- Search across all indexed documentationget_index_status()- Check indexing status and cache statistics
Development
Running the server
HTTP mode (Production/Smithery):
uv run python -m src.mainSTDIO mode (Local development):
uv run python server.pyContainer mode:
docker build -t prisma-docs-server .
docker run -p 8081:8081 -e PORT=8081 prisma-docs-serverInstalling dependencies
uv syncProject structure
prisma-cloud-docs-mcp-server/
├── src/
│ ├── main.py # HTTP MCP server implementation
│ └── middleware.py # Configuration middleware for Smithery
├── server.py # Legacy STDIO server (for local development)
├── pyproject.toml # Project configuration
├── uv.lock # Dependency lock file
├── Dockerfile # Container deployment
├── smithery.yaml # Smithery container configuration
└── README.md # This fileLicense
MIT License - see LICENSE file for details.
Contributing
Fork the repository
Create a feature branch
Make your changes
Test with Claude Desktop
Submit a pull request
Troubleshooting
Server not starting in Claude Desktop
Ensure
uvis installed and in your PATHVerify the path to the project directory is correct
Check Claude Desktop logs for specific error messages
Missing dependencies
Run uv sync to ensure all dependencies are installed.
Documentation not found
The server needs to index documentation first. Use the index_prisma_docs or index_prisma_api_docs tools before searching.
Available Tools
6 toolsget_index_statusA
Check how many documents are currently cached.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the tool checks cache status, which implies a read-only, non-destructive operation, but doesn't add details like rate limits, auth needs, or what 'cached' entails. It's adequate but lacks rich 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 that directly states the tool's purpose with zero waste. It's appropriately sized and front-loaded, making it easy to understand quickly.
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 has 0 parameters, 100% schema coverage, and an output schema exists, the description is reasonably complete. It covers the core purpose, but for a tool with no annotations, it could add more context on behavior or output, though the output schema mitigates this.
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 tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add param info, which is fine here, but since there are no params, it doesn't fully compensate for any gaps, so it scores just below the maximum.
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 ('Check') and resource ('documents currently cached'), providing a specific purpose. However, it doesn't differentiate from sibling tools like 'search_all_docs' or 'index_prisma_docs', which might also relate to document status or indexing operations, so it doesn't reach the highest 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 offers no guidance on when to use this tool versus alternatives like 'search_all_docs' or 'index_prisma_docs', nor does it mention prerequisites or exclusions. It implies usage for checking cache status but lacks explicit context or comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
index_prisma_api_docsA
Index Prisma Cloud API documentation. Call this first before searching.
| Name | Required | Description | Default |
|---|---|---|---|
| max_pages | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
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 mentions indexing but doesn't explain what indexing entails (e.g., data fetching, processing, storage), potential side effects, rate limits, or authentication needs. The directive to call it first hints at initialization behavior but lacks detail on outcomes or errors.
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 two short sentences that are front-loaded and waste no words. Every sentence serves a clear purpose: stating the action and providing usage guidance.
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 has an output schema (which reduces the need to describe return values) and only one parameter, the description is somewhat complete for its simplicity. However, as a tool with no annotations and a parameter lacking schema descriptions, it should provide more context on behavior and parameter meaning to be fully helpful.
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 one parameter ('max_pages') with 0% description coverage in the schema, so the description must compensate. However, the description provides no information about parameters, not even mentioning 'max_pages' or its purpose. Since there's only one parameter, the baseline is higher, but the description adds no 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 ('Index Prisma Cloud API documentation') and provides a specific directive ('Call this first before searching'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from its sibling 'index_prisma_docs', which appears similar, leaving some ambiguity about when to use one versus the other.
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 explicitly states 'Call this first before searching,' providing clear guidance on when to use this tool in relation to search operations. It implies a prerequisite step for searching, though it doesn't specify alternatives or exclusions beyond this sequencing advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
index_prisma_docsA
Index Prisma Cloud documentation. Call this first before searching.
| Name | Required | Description | Default |
|---|---|---|---|
| max_pages | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
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. While it mentions that this should be called 'first before searching' (implying it's a setup/preparation step), it doesn't describe what 'indexing' actually does (e.g., whether it crawls/scrapes documentation, builds a search index, stores data locally/remotely), what happens if called multiple times, or any performance/rate limit considerations.
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 two short sentences that each serve a clear purpose: stating the action and providing usage guidance. There's no wasted language or 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 that there's an output schema (which presumably describes the return values), the description doesn't need to explain return values. However, for an indexing tool with no annotations and a parameter that lacks explanation, the description should provide more context about what indexing entails and how the parameter affects the operation to be truly 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?
The schema has 1 parameter with 0% description coverage, so the description must compensate. The description provides no information about the 'max_pages' parameter - it doesn't explain what pages are being indexed, what happens when the limit is reached, or typical values. This leaves the parameter's purpose and usage unclear.
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 ('Index') and resource ('Prisma Cloud documentation'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from its sibling 'index_prisma_api_docs', which appears to serve a similar indexing function for API docs specifically.
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 explicit guidance on when to use this tool ('Call this first before searching'), which clearly distinguishes it from the search-related sibling tools. This tells the agent the proper sequence of operations in the workflow.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_all_docsC
Search across all Prisma Cloud documentation sites.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
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. The description only states what the tool does at a high level ('Search across all Prisma Cloud documentation sites') but doesn't disclose any behavioral traits such as search scope limitations, performance characteristics, authentication requirements, rate limits, or what the output contains. This leaves significant gaps for an agent trying to understand how to use this tool effectively.
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 - a single sentence that directly states the tool's purpose. There's no wasted language or unnecessary elaboration, making it front-loaded and efficient. Every word earns its place in conveying 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 that there's an output schema (which means the description doesn't need to explain return values), the description provides the minimum viable information about what the tool does. However, for a search tool with no annotations and 0% schema description coverage, the description should do more to explain search behavior, scope, and limitations to be truly complete for agent 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 input schema has 0% description coverage, with only a single parameter 'query' documented as a string. The description provides no additional information about parameter semantics - it doesn't explain what type of search query is expected, syntax requirements, or any constraints. With low schema coverage, the description fails to compensate for the lack of 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 ('Search') and the resource ('across all Prisma Cloud documentation sites'), which provides a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'search_prisma_api_docs' or 'search_prisma_docs', which appear to be more targeted 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 provides no guidance on when to use this tool versus alternatives. With sibling tools like 'search_prisma_api_docs' and 'search_prisma_docs' available, there's no indication of what makes this tool different or when it should be preferred over those more specific options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_prisma_api_docsC
Search Prisma Cloud API documentation
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states what the tool does at a high level, without mentioning any behavioral traits like authentication requirements, rate limits, response format, pagination, or error handling. 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 extremely concise with just one sentence that directly states the tool's purpose. There's zero waste or unnecessary information, making it front-loaded and efficient for the agent 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 tool has an output schema (which handles return values) and only one simple parameter, the description's minimal approach is somewhat adequate. However, with no annotations and multiple similar sibling tools, the description should provide more context about scope and differentiation to be truly 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?
The schema has 0% description coverage for its single parameter 'query', and the tool description provides no additional information about what the query parameter should contain, its format, or examples of valid values. The description doesn't compensate for the complete lack of parameter documentation in 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 tool's purpose as 'Search Prisma Cloud API documentation', which is a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'search_prisma_docs' or 'search_all_docs', leaving some ambiguity about scope and 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 'search_prisma_docs' or 'search_all_docs'. There's no mention of prerequisites, context, or exclusions, leaving the agent with no usage direction beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_prisma_docsC
Search Prisma Cloud documentation
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states the basic function without mentioning search behavior (e.g., ranking, filters, pagination), performance characteristics, or any constraints. This is inadequate for a search tool with zero annotation coverage.
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 text. It's front-loaded with the core purpose, though this brevity comes at the cost of completeness.
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 presence of an output schema (which handles return values), the description's minimalism is somewhat mitigated. However, for a search tool with 1 parameter, 0% schema coverage, and no annotations, it fails to provide adequate context about behavior, usage, or parameter meaning, making it incomplete for effective tool selection.
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 0%, and the description adds no parameter information beyond what's implied by the tool name. It doesn't explain the 'query' parameter's format, syntax, or semantics, leaving the single required parameter undocumented in both schema and 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?
The description 'Search Prisma Cloud documentation' clearly states the action (search) and target resource (Prisma Cloud documentation), providing basic purpose. However, it doesn't distinguish this tool from sibling tools like 'search_all_docs' or 'search_prisma_api_docs', leaving ambiguity about scope and 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 'search_all_docs' or 'search_prisma_api_docs'. There's no mention of context, prerequisites, or exclusions, leaving the agent to infer usage from 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.
6 tool updates
- First observed
get_index_status - First observed
index_prisma_api_docs - First observed
index_prisma_docs - First observed
search_all_docs - First observed
search_prisma_api_docs - First observed
search_prisma_docs
TDQS
The tools have some overlap that could cause confusion, particularly between the three search tools (search_all_docs, search_prisma_api_docs, search_prisma_docs) and the two index tools (index_prisma_api_docs, index_prisma_docs). However, the descriptions clarify the scope of each, helping to distinguish them. The get_index_status tool is clearly distinct in purpose.
All tool names follow a consistent verb_noun pattern with snake_case throughout, such as get_index_status, index_prisma_api_docs, and search_all_docs. This predictability makes it easy for agents to understand and use the tools without confusion.
With 6 tools, the server is well-scoped for its purpose of indexing and searching Prisma Cloud documentation. Each tool serves a clear function, and the count is neither too sparse nor overwhelming, fitting typical expectations for a documentation-focused MCP server.
The tool set covers the core workflows of indexing and searching documentation, with separate tools for API and general docs, plus a status check. A minor gap is the lack of tools for managing or updating indexed content, but agents can work around this by re-indexing as needed.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Official MCP server for Qase — manage test cases, runs, suites, defects via AI tools.
Official Microsoft Learn MCP Server – real-time, trusted docs & code samples for AI and LLMs.
Official MCP server for Certifier to issue, manage, and track certificates and badges.
Related MCP Servers
- PythonApache 2.0
- AlicenseNot gradedqualityAmaintenanceOfficial MCP server for the s2.dev serverless stream platform13535MIT
- AlicenseBqualityBmaintenanceMCP server for asking questions about Cortex Cloud documentation64MIT

Nhost MCP Serverofficial
AlicenseNot gradedqualityFmaintenanceOfficial MCP server for the Nhost backend platform. Manage Postgres data, GraphQL, auth, storage, migrations and Hasura metadata via AI assistants.5MIT
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/clarkemn/prisma-cloud-docs-mcp-server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server