by clarkemn
Easily search Prisma Cloud docs, including API documentation, for Dropbox shared file help. Find quick, structured resul
Searches Prisma Cloud documentation and API references directly from Claude, with caching and relevance scoring for fast results.
Prisma Cloud Docs is a community-built MCP server published by clarkemn that provides AI assistants with tools and capabilities via the Model Context Protocol. Easily search Prisma Cloud docs, including API documentation, for Dropbox shared file help. Find quick, structured resul It is categorized under productivity.
You can install Prisma Cloud Docs in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Prisma Cloud Docs is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
Prisma Cloud Docs has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
I recommend Prisma Cloud Docs for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Useful MCP listing: Prisma Cloud Docs is the kind of server we cite when onboarding engineers to host + tool permissions.
We wired Prisma Cloud Docs into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
According to our notes, Prisma Cloud Docs benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Prisma Cloud Docs is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Prisma Cloud Docs reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Prisma Cloud Docs reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Prisma Cloud Docs reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Prisma Cloud Docs is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
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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.
No installation needed! Just use uvx in your Claude Desktop configuration.
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 claude
curl -LsSf https://astral.sh/uv/install.sh | sh
git clone https://github.com/clarkemn/prisma-cloud-docs-mcp-server.git
cd prisma-cloud-docs-mcp-server
uv sync
Add this server to your Claude Desktop configuration file:
Location: ~/Library/Application Support/Claude/claude_desktop_config.json (macOS)
{
"mcpServers": {
"Prisma Cloud Docs": {
"command": "uvx",
"args": ["prisma-cloud-docs-mcp-server@latest"],
"env": {},
"transport": "stdio"
}
}
}
{
"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.
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.py
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 statisticsuv run python -m src.main
uv run python server.py
docker build -t prisma-docs-server .
docker run -p 8081:8081 -e PORT=8081 prisma-docs-server
uv sync
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 file
MIT License - see LICENSE file for details.
uv is installed and in your PATHRun uv sync to ensure all dependencies are installed.
The server needs to index documentation first. Use the index_prisma_docs or index_prisma_api_docs tools before searching.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.