CodeSeeker is a four-layer hybrid search and knowledge graph tool designed for AI coding assistants, enabling them to understand codebases through indexing and semantic search. It combines BM25, vector embeddings, RAPTOR directory summaries, and graph expansion for enhanced code navigation.
From the registry: Graph-powered code intelligence with semantic search and knowledge graph for AI assistants
Please install the `codeseeker` MCP server into my current AI client (that's you).
Required prerequisites (do these first if not already done):
- **Node.js 18+** — Required to run via npx.
Canonical MCP server config (stdio transport):
- command: `npx`
- args: ["-y","codeseeker","serve","--mcp"]
Note: Zero-config — auto-indexes on first use.
Add this MCP server to my current client's config in the correct format for you. If you need secrets or credentials I haven't provided, ASK me — do not invent values or leave raw placeholders. After adding it, tell me how to verify the server is connected.Real-time infrastructure monitoring with metrics, logs, alerts, and ML-based anomaly detection.
Validate oh-my-posh configurations and segment snippets against the official schema.
Real-time Kubernetes network traffic visibility and API analysis for HTTP, gRPC, Redis, Kafka, DNS.