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Query a company knowledge base and get accurate answers from internal documents.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-business-bot" yet — see the docs or source repo.
Please answer based on the internal company knowledge base: What is the employee leave process? If there are relevant policy documents, summarize the key steps.
An accurate answer grounded in internal policy documents, summarizing the key leave process steps.
Search the company knowledge base for this product's documentation and answer which core capabilities it supports.
A feature summary and list of core capabilities compiled from internal product documents.
Based on internal documents, answer: What steps must a new employee complete during onboarding? List them in order.
An ordered onboarding checklist organized from internal process documents.
Office workers can ask the company knowledge base directly when they need policies, procedures, or internal references, and receive answers grounded in internal documents.
Product managers or researchers can use RAG-powered retrieval to quickly locate internal product descriptions, project documents, and accumulated knowledge, then extract answers.
It is an MCP tool for querying a company knowledge base with RAG and providing accurate answers based on internal documents.
Based on the provided information, it answers questions primarily using internal company documents and knowledge base content.
The provided material does not include installation steps, runtime details, or key requirements. Please see the source repository for specifics.
Serve local knowledge bases to MCP agents for search, listing, and document retrieval.
Expose internal company services as tools for AI-driven business operations.
Search enterprise documents in natural language across PDF, PPT, and Word files.
Production-ready MCP server for query normalization, retrieval, and RAG prompt building.
Manage project knowledge and requirements with fast full-text search and updates.
Centralize knowledge, run semantic search, ingest documents, and generate RAG answers.