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Search and add traceable RAG knowledge for each project workspace.
The available material is sparse and indicates an MCP tool for per-project access to and modification of a RAG knowledge base. No keys or remote endpoints are declared, and it is MIT-licensed open source, so overall risk appears low, but caution is still warranted because it executes code and likely reads/writes local knowledge-base data, with unclear maintenance status.
The material explicitly states that no keys or environment variables are required, and no token handling, credential storage, or account authorization flow is described, indicating low credential exposure risk.
No remote endpoints are declared, and the description does not mention external APIs, cloud services, or telemetry uploads; based on the provided material, no clear data egress path is evident.
The system checks indicate that this tool executes code. That is a normal capability for MCP tools, but the material does not specify what processes it may start or what system capabilities it uses, so it should be run in a constrained environment and verified in practice.
Its functionality includes searching and adding knowledge chunks, which likely requires reading from and writing to project-level RAG knowledge-base data. The material does not specify exact paths, storage locations, or permission boundaries, so this warrants caution, though there is no clear sign of overbroad access.
There is an auditable open-source GitHub repository with an MIT license, which is a meaningful risk-reducing factor. However, the source is a third-party registry, community adoption is 0 stars, and maintenance status is unknown, so trust is only moderate and source/dependency review is advisable before installation.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-rag" yet — see the docs or source repo.
Search the RAG knowledge base for the project "Payment Platform Refactor" for "refund process exception handling". Return the 5 most relevant knowledge chunks with source and timestamp.
A list of relevant knowledge chunks with summaries, relevance, source details, and traceable timestamps.
Add the following as a new knowledge chunk to the project "Mobile App Redesign" knowledge base: "In Q2 2025, prioritize the homepage navigation update, with A/B test metrics of next-day retention and click-through rate," and record the source as product review meeting notes.
A confirmation that a source-tagged knowledge chunk was added, including an entry ID or write result.
Using the knowledge base for the project "Enterprise Knowledge Assistant," answer "Which document import formats are currently supported?" and cite the source chunk for each conclusion so the answer is traceable.
A cited answer that clearly maps each conclusion to its supporting knowledge source.
Turn unstructured documents into a searchable knowledge base for AI agents.
Centralize knowledge, run semantic search, ingest documents, and generate RAG answers.
Intelligent RAG tool that chooses between private knowledge and web search.
Index documents and retrieve relevant context for better LLM responses.
Use authenticated MCP tools for graph-augmented and hybrid RAG retrieval.
Expose modular retrieval and reasoning tools to AI assistants through MCP.