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cti-mcp-server

by TopCaver

CTI MCP Server

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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.

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