A
licenseA
qualityD
maintenanceProvides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
7
9 npm
1
MIT
Mock Documentation MCP Server
by anupmurali05
Click on "Deploy 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., "@Mock Documentation MCP Serverfind documentation about authentication"
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.
MCP Server
This repository contains a FastMCP server that exposes a mocked documentation database tool.
Tool
get_documentation_from_database(document_id: str | None = None, query: str | None = None) -> dict
This tool returns mocked documentation records from a simulated database. You can request a specific document by document_id or search the mocked documentation with query.
Related MCP server: Reflex Docs MCP Server
Run the server
Install dependencies in the project virtual environment:
cd /Users/anupmurali/projects/MCP
.venv/bin/python -m pip install -e ./mcp-serverRun the server:
cd /Users/anupmurali/projects/MCP/mcp-server
.venv/bin/python main.pyThe MCP endpoint will be available at http://127.0.0.1:8000/mcp.
Test the tool locally
You can call the tool directly from Python for a quick smoke test:
cd /Users/anupmurali/projects/MCP/mcp-server
.venv/bin/python -c "from main import get_documentation_from_database; print(get_documentation_from_database(query='MCP'))"Notes
The server uses
fastmcpwithmcpunder the hood.The mocked database includes a few sample documentation records.
This server cannot be deployed
Maintenance
ActivityInactive
ResponsivenessNo issues
Related MCP Connectors
Versioned documentation registry and semantic search for AI tools and coding assistants.
Retrieve information from the Medusa documentation to assist you with your Medusa development.
Query any docs site via MCP. Submit a URL, ask questions, get cited answers.
Docs Q&A: search 169 data and AI guides, fetch any page as markdown. Read-only, keyless.
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