RCA-MCP

RCA-MCP Connector

Note: the api.rca-mcp.com custom domain isn't wired up yet — point

RCA_MCP_API_URL at the current backend URL below instead.

What is RCA-MCP?

The only MCP server purpose-built for causal Root Cause Analysis. 56 tools covering causal graph construction, 10 RCA model families plus 3 dedicated PyRCA algorithms (Salesforce PyRCA, BSD-3-Clause), multi-model consensus, and PDF/HTML/Excel/Markdown report generation. Works with Claude, Ollama, Groq, OpenAI, Gemini, LangChain, Cursor — 10 providers.

Quick Start (2 minutes)

rca-mcp-connector is a published PyPI package — no clone needed. Point any MCP client at it with uvx (or pip install rca-mcp-connector if you'd rather manage the install yourself):

uvx rca-mcp-connector

Get a free API key at rcamcp.datalizedglb.cloud — no credit card required — then set RCA_MCP_API_KEY in your MCP client's config (examples below).

Claude Code Setup

Add to .mcp.json in your workspace root:

{

"mcpServers": { "rca-mcp": { "command": "uvx", "args": ["rca-mcp-connector"], "env": { "RCA_MCP_API_URL": "https://rcamcp-production.up.railway.app", "RCA_MCP_API_KEY": "your_api_key_here" } } } }

Ollama Setup

go install github.com/mark3labs/mcphost@latest

mcphost -m ollama:qwen3:14b --config providers/mcp-servers.json

OpenAI Agents SDK

from agents import Agent, MCPServerStdio

import asyncio

async def main(): async with MCPServerStdio( params={ "command": "uvx", "args": ["rca-mcp-connector"], "env": { "RCA_MCP_API_URL": "https://rcamcp-production.up.railway.app", "RCA_MCP_API_KEY": "your_api_key_here", }, } ) as rca_server: agent = Agent(name="RCA Agent", model="gpt-4o", mcp_servers=[rca_server]) result = await agent.run("Find the root cause of the API latency spike.") print(result.final_output)

asyncio.run(main())

LangChain

from langchain_mcp_adapters.client import MultiServerMCPClient

from langchain_anthropic import ChatAnthropic from langgraph.prebuilt import create_react_agent import asyncio

async def main(): async with MultiServerMCPClient({ "rca-mcp": { "command": "uvx", "args": ["rca-mcp-connector"], "env": { "RCA_MCP_API_URL": "https://rcamcp-production.up.railway.app", "RCA_MCP_API_KEY": "your_api_key_here", }, "transport": "stdio", } }) as client: tools = await client.get_tools() agent = create_react_agent(ChatAnthropic(model="claude-sonnet-4-6"), tools) result = await agent.ainvoke({"messages": [{"role": "user", "content": "Run an FMEA analysis"}]}) print(result"messages".content)

asyncio.run(main())

See providers/ for ready-to-use config templates and full examples (Groq, Gemini, OpenRouter, Claude Desktop).

Third-Party Licences

PyRCA (Salesforce): BSD-3-Clause Copyright (c) 2022, salesforce.com, inc. https://github.com/salesforce/PyRCA

Algorithms in rca_pyrca_* tools are independently-written adaptations of PyRCA's published methods (Zheng et al. 2023, arXiv:2306.11417), not direct copies of PyRCA source code, per the private API's models/pyrca_adapter.py.

Citing RCA-MCP

@software{rcamcp2026,

title = {RCA-MCP: An MCP Server for Causal Root Cause Analysis}, author = {dave1362}, year = {2026}, url = {https://github.com/dave1362/rca-mcp-connector}, note = {v4.1.20} }