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Causality MCP

Rust MCP server for Claude Desktop: ingest offline logs (files/Docker), find root causes, and export trace timelines (HTML/Markdown/CSV).

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About Causality MCP

Causality MCP is an MCP server in the Files category: rust MCP server for Claude Desktop: ingest offline logs (files/Docker), find root causes, and export trace timelines (HTML/Markdown/CSV). It has been installed 0 times through Conduid.

Install

Clone
git clone https://github.com/j4flmao/causality-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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README

causality-mcp

causality-mcp is a Rust workspace that provides a local MCP server for Claude Desktop plus the ingestion + causal analysis engine behind it.

It is designed for “no-instrumentation” diagnosis: ingest the logs you already have (local files or Docker containers), then ask Claude to explain root cause and causality.

Repository layout

  • crates/: Rust workspace crates (reusable libraries + MCP server binary)
  • docs/: user-facing guides and copy/paste prompt packs
  • docker/test-server/: Docker fixtures and remote-log mirror container recipes
  • .github/: CI/release workflows and GitHub templates
  • causality.toml: default configuration used by the MCP server

Requirements

  • Rust 1.94 (pinned via rust-toolchain.toml)
  • Docker Desktop (optional but recommended for container log workflows)

Add to Claude Desktop (2 ways)

You can run the MCP server either by installing from crates.io (recommended for end users) or by running a locally built .exe.

Option 1: Install from crates.io

Install the binary:

cargo install causality-mcp-server

Then configure Claude Desktop to run the installed executable:

{
  "mcpServers": {
    "causality-mcp": {
      "command": "causality-mcp",
      "args": [
        "--config",
        "D:\\\\path\\\\to\\\\causality.toml",
        "--log-level",
        "info"
      ],
      "env": {
        "LOG_CAUSALITY_DOCKER_CMD": "C:\\\\Program Files\\\\Docker\\\\Docker\\\\resources\\\\bin\\\\docker.exe"
      }
    }
  }
}

Option 2: Build and run the .exe

Build from source:

cargo build --release -p causality-mcp-server

Windows output:

  • target/release/causality-mcp.exe

Claude Desktop config:

{
  "mcpServers": {
    "causality-mcp": {
      "command": "D:\\\\path\\\\to\\\\target\\\\release\\\\causality-mcp.exe",
      "args": [
        "--config",
        "D:\\\\path\\\\to\\\\causality.toml",
        "--log-level",
        "info"
      ],
      "env": {
        "LOG_CAUSALITY_DOCKER_CMD": "C:\\\\Program Files\\\\Docker\\\\Docker\\\\resources\\\\bin\\\\docker.exe"
      }
    }
  }
}

Restart Claude Desktop after editing claude_desktop_config.json.

MCP tools (current)

The MCP server currently documents Docker-first workflows (direct SSH ingestion prompts are planned / coming soon).

Tools:

  • discover_docker_logs
  • ingest_logs
    • Local: source glob
    • Docker: docker_container + docker_path
  • find_root_cause
  • trace_request
  • correlate_services
  • export_timeline (markdown, csv, html)

Examples

Discover likely log files in a container:

{
  "name": "discover_docker_logs",
  "arguments": {
    "docker_container": "my-container",
    "roots": ["/var/log", "/app/logs", "/logs"],
    "limit": 200
  }
}

Ingest container logs:

{
  "name": "ingest_logs",
  "arguments": {
    "docker_container": "my-container",
    "docker_path": "/var/log/app/*.log",
    "format": "auto"
  }
}

Ingest local file logs:

{
  "name": "ingest_logs",
  "arguments": {
    "source": "D:/logs/myapp/**/*.log",
    "format": "auto"
  }
}

Find root causes:

{
  "name": "find_root_cause",
  "arguments": {
    "error_pattern": "error|exception|panic|failed|timeout|5\\\\d\\\\d",
    "window_secs": 300,
    "max_candidates": 10
  }
}

Export an HTML timeline:

{
  "name": "export_timeline",
  "arguments": {
    "trace_id": "t2",
    "format": "html"
  }
}

Remote server logs (Docker mirror)

If you want to analyze logs on a remote server without running the MCP server on that server, use the Docker “mirror” container:

It connects to your server and mirrors selected log files into /var/log/remote inside the container. You then ingest /var/log/remote/*.log using the Docker tools.

Direct SSH ingestion tools are not documented here (planned / coming soon).

Docs

README mirrored from the source repository 5 months ago. The original is authoritative.

Questions

About Causality MCP

How do I install Causality MCP?

Run git clone https://github.com/j4flmao/causality-mcp, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is Causality MCP safe to use with an AI agent?

Its trust score is 34 out of 100 (low). Conduid hasn't run static security checks on this repository yet, so review the source yourself before granting it credentials. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Causality MCP still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.