README

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?"

conduit-mcp

README

conduit-mcp

What It Does

Setup

1. Install

2. Configure for Claude Code

3. Use

Environment Variables

Conversational Threads

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