MiniRAG
An MCP server wrapper around MiniRAG that provides efficient retrieval-augmented generation capabilities through two distinct approaches: naive vector database querying and smart graph-based retrieval using entity relationships and reasoning paths. Leverages client-managed LLM inference with structured output constraints for enhanced reliability, while simplifying MiniRAG setup through UV dependency management. Supports configurable embedding providers including Ollama and OpenAI-compatible services, returning answers with cited sources in JSON format for knowledge retrieval workflows optimized for small language models.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-01.
Scan details: Circle-IR · 2026-09-01 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Repository
- github.com/witwicki/minirag-mcp
- Author type
- human
- Last scanned
- 2026-09-01
- Updated
- 2026-09-01
Use via MCP
Resolve MiniRAG from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp --scope user for --scope project to commit it to .mcp.json.