Point Server

MCP server for the Point Knowledge API — verified, citable knowledge for AI coding assistants.

Point indexes curated technical documentation (RFCs, framework docs, standards, API references) and makes it searchable with hybrid search (BM25 + vector) and precise citations. This MCP server gives your AI assistant direct access to that knowledge.

Tools

Tool	Description	Tokens
search	Hybrid search with citations and relevance scores	~200/result
get_document_toc	Lightweight table of contents for a document	~50
get_sections	Load specific sections by chunk ID (max 50)	varies
list_collections	Browse or search available knowledge collections	~100/collection
get_document_full	Full markdown content of a document	varies (can be large)

Recommended workflow: search or list_collections to find content, then get_document_toc for structure, then get_sections for specific passages. Use get_document_full only when you need the complete text.

Prerequisites

1. Python 3.11+ installed
2. Point API key — get one free at pinchpoint.dev/point/keys

Installation

pip install point-mcp

Or install from source:

git clone https://github.com/mcdonaldsam/point-mcp.git
cd point-mcp
pip install -e .

Setup by IDE

Claude Code

Add to your Claude Code MCP settings (~/.claude/settings.json or project .claude/settings.json):

{
  "mcpServers": {
    "point": {
      "command": "point-mcp",
      "env": {
        "POINT_API_KEY": "your-api-key-here"
      }
    }
  }
}

Or add via CLI:

claude mcp add point -- point-mcp -e POINT_API_KEY=your-api-key-here

Cursor

Add to your Cursor MCP config (~/.cursor/mcp.json):

{
  "mcpServers": {
    "point": {
      "command": "point-mcp",
      "env": {
        "POINT_API_KEY": "your-api-key-here"
      }
    }
  }
}

Windsurf

Add to your Windsurf MCP config (~/.windsurf/mcp.json):

{
  "mcpServers": {
    "point": {
      "command": "point-mcp",
      "env": {
        "POINT_API_KEY": "your-api-key-here"
      }
    }
  }
}

VS Code (GitHub Copilot)

Add to your VS Code settings (.vscode/mcp.json in your project, or user settings):

{
  "servers": {
    "point": {
      "type": "stdio",
      "command": "point-mcp",
      "env": {
        "POINT_API_KEY": "your-api-key-here"
      }
    }
  }
}

Using uvx (no install needed)

If you have uv installed, you can run point-mcp without installing it globally:

{
  "mcpServers": {
    "point": {
      "command": "uvx",
      "args": ["point-mcp"],
      "env": {
        "POINT_API_KEY": "your-api-key-here"
      }
    }
  }
}

Manual / Other Tools

Any MCP client that supports stdio transport:

POINT_API_KEY=your-api-key-here point-mcp

Configuration

Environment Variable	Required	Default	Description
POINT_API_KEY	Yes	—	Your Point API key (get one)
POINT_API_URL	No	https://point-api.pinchpoint.dev	API base URL (for self-hosted or local dev)

Examples

Once configured, your AI assistant can use Point tools naturally:

"Search Point for how OAuth 2.0 PKCE works"

"What collections does Point have about cloud infrastructure?"

"Get the table of contents for document rfc-7636, then load sections 2 and 3"

The assistant will automatically use the appropriate tools and include citations in its responses.

Development

# Clone and install with dev dependencies
git clone https://github.com/mcdonaldsam/point-mcp.git
cd point-mcp
pip install -e ".[dev]"

# Run tests
pytest

# Run server locally
POINT_API_KEY=your-key point-mcp

License

MIT