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datakailabs
by datakailabs

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

Related MCP server: ckg-mcp

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?"
A
license - permissive license
-
quality - not tested
C
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

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If you are the server author, to access and configure the admin panel.

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