cti-mcp-server

cti-mcp-server

Provides threat intelligence tools like IoC lookups, event backtracking, and IP enrichment via MCP, enabling automated triage and evidence queries.

Category
Visit Server

README

CTI MCP Server

中文En

CTI MCP Server is a lightweight MCP (Message/Tool Call Protocol) service framework that packages and exposes multiple tools for a Threat Intelligence Agent, enabling automated triage, evidence queries, and centralized integration.

Key Features

  • Lightweight: uses fastmcp to wrap tools as remotely callable MCP methods.
  • TI-focused: built-in IoC lookups, event backtracking, and basic IP enrichment.
  • Model-integrated: works with OpenAI and other LLMs so the model can call MCP tools during analysis to gather evidence.
  • Easy to debug and deploy locally with CLI (Typer) support.

Quick Start

Prepare Python (project requires Python >= 3.14) and create a virtual environment:

python -m venv .venv
source .venv/bin/activate
pip install -e .

Start the MCP SSE service (defaults to 127.0.0.1:8000, path /mcp):

uv run cti-mcp-server start
# or
python -m cti_mcp_server.server start

Custom host/port/path example:

cti-mcp-server start --host 0.0.0.0 --port 8000 --path /mcp

Enable authentication (recommended for public internet exposure):

export CTI_MCP_AUTH_TOKEN="replace-with-a-long-random-token"
cti-mcp-server start --host 0.0.0.0 --port 8000 --path /mcp

You can also pass it directly:

cti-mcp-server start --auth-token "replace-with-a-long-random-token"

When auth is enabled, clients must send header:

Authorization: Bearer <your-token>

Validate locally with the Agent example (connects to local MCP service):

cti-agent 8.8.8.8

Use custom model endpoint / key / model (OpenAI-compatible API):

cti-agent 8.8.8.8 \
	--mcp-url http://127.0.0.1:8000/mcp \
	--llm-base-url http://127.0.0.1:11434/v1 \
	--llm-api-key ollama \
	--model qwen3:latest

cti-agent command arguments:

  • Positional argument: ioc (required), e.g. IP/domain.
  • --mcp-url: MCP service URL (default http://127.0.0.1:8000/mcp).
  • --llm-base-url: OpenAI-compatible model API base URL.
  • --llm-api-key: API key for the model endpoint.
  • --model: model name (for example qwen3:latest).

Built-in MCP Tools (Examples)

  • ioc_type(ioc: str) -> str: Detects IoC type (IP / domain).
  • local_summary(ioc: str) -> dict: Returns structured summary from the local intel store (verdict, tags, first_seen, etc.).
  • local_events(ioc: str, limit: int=20) -> dict: Returns recent observed events (for evidence lists).
  • ip_basic(ip: str) -> dict: Offline basic IP enrichment (private/public determination, geo/ASN placeholder info).

Development & Testing

  • Run tests: pytest
  • Lint/format: ruff .
  • Dependency management and packaging via pyproject.toml.

Contributing

Issues and PRs are welcome. Please describe the problem and purpose of changes in the PR, keep commits tidy, provide test coverage, and include a brief explanation.

License

See the LICENSE file in the repository (or otherwise negotiated if absent).


Thanks for using CTI MCP Server. For help, please open an issue in the repository.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured