conduit-mcp

MCP server that gives AI agents access to the Conduit knowledge graph.

What It Does

Any AI agent that supports MCP (Claude Code, Pi, OpenCode, Cursor, etc.) can query your organization's knowledge graph through three tools:

Tool	Purpose
conduit_ask	Ask a question, get a synthesized answer with sources
conduit_context	Retrieve raw knowledge units with graph relationships
conduit_search	Quick semantic search — titles and scores only
conduit_health	Check server connectivity

Setup

1. Install

pip install conduit-mcp

2. Configure for Claude Code

Add to your ~/.claude/settings.json:

{
  "mcpServers": {
    "conduit": {
      "command": "python",
      "args": ["-m", "server"],
      "cwd": "/path/to/conduit-mcp",
      "env": {
        "CONDUIT_ENDPOINT": "http://localhost:4000",
        "CONDUIT_API_KEY": "your-api-key"
      }
    }
  }
}

3. Use

In Claude Code (or any MCP-capable agent):

> Ask Conduit how Snowflake Cortex Search works

[calls conduit_ask with query="How does Snowflake Cortex Search work?"]

Environment Variables

Variable	Default	Description
CONDUIT_ENDPOINT	http://localhost:4000	Conduit server URL
CONDUIT_API_KEY	(empty)	API key for authentication
CONDUIT_KAI_ID	(none)	Optional Kai ID to scope all queries

Conversational Threads

The conduit_ask tool supports thread_id for follow-up questions:

First: conduit_ask("What is Delta Live Tables?", thread_id="abc-123")
Then:  conduit_ask("Can I use it with Cortex?", thread_id="abc-123")
       → automatically rewritten to: "Can I use Delta Live Tables with Snowflake Cortex?"