MCP Overview | KINETK Graph Service API

The kinetk MCP server is a Model Context Protocol server that exposes the KINETK Knowledge Graph as tools inside your AI assistant. Mention kinetk in a prompt and the assistant browses trending narratives, walks the visual pattern map and runs live retrieval jobs for you, getting back token-efficient answers.

Two ways to run it

	Hosted MCP (recommended)	Local MCP (advanced, self-run)
What it is	A managed endpoint KINETK runs for you	The `kinetk-mcp` package you run as a subprocess
Setup	Nothing to install — sign in, or pass an `x-api-key` header	Clone, build, and point your client at it
Tools	The full set: context jobs, narratives, patterns, search/fetch	The three original context-job tools only
Best for	Claude Desktop, ChatGPT, Claude Code, Codex, Cursor, Gemini, Grok	Pinning a specific build, or custom forks
Guide	Hosted MCP Setup	Local MCP (Advanced)

Most users want the Hosted MCP: it is always current and has every tool. Both bill the same account at the same prices as the HTTP API.

What you can do with it

Ask your assistant what’s trending, dig into a narrative, run a full analysis, explore what content looks like, or pull posts to cite. See What You Can Ask for example prompts and what each costs.

When to use the MCP vs the API

Use case	Pick
You work in an AI assistant and want it to fetch live context	MCP
You’re exploring a topic conversationally — trending, drill-down, related patterns	MCP
You’re building a backend, scheduled job or dashboard	API
You need `POST /search`, `stats` jobs, `GET /usage` or `GET /health`	API — these aren’t exposed as tools

Why slim results?

Full results can run to hundreds of kilobytes, and assistants pay per token. The job tools return a slim, LLM-optimized envelope by default; ask for verbose: true on kinetk_get_context_job_result when you need the full payload.