Developing Documentation MCP Servers for IBM Bob
Summary
This post details the development of Documentation MCP (Model-Controlled Program) Servers for IBM Bob, an AI-based development tool. These servers are crucial because large language models are often outdated upon release, and software documentation changes frequently. The article describes re-implementing the Orchestrate Documentation MCP Server as a learning exercise, which features two primary tools. The "search" tool performs a hybrid semantic and keyword search, returning concise, section-level results with metadata like title, link, and line range. The "query_docs" tool acts as a read-only virtual file system, allowing agents to access specific document sections using standard shell commands such as 'head' and 'tail', thereby preventing context window overflow. The goal was to efficiently break down large documents by markdown sections. LanceDB, a lightweight search engine, was used for the implementation, which can be customized by placing markdown documents in a 'documentation' folder.
Key takeaway
For AI Engineers building agents that require current technical documentation, relying solely on LLM training data is insufficient. You should implement Model-Controlled Program (MCP) servers with a two-stage approach: a hybrid search tool returning concise, section-level metadata, and a virtual file system tool for precise content retrieval. Prioritize designing these tools to manage context windows effectively by enabling agents to query specific document sections using commands like `head` and `tail`.
Key insights
MCP servers provide AI agents with current, precise documentation access via structured search and virtual file system tools.
Principles
- LLMs need current documentation due to training data age and software changes.
- Efficient agent tools return concise, section-level documentation results.
- Virtual file systems enable precise documentation querying, reducing context usage.
Method
Implement a hybrid search tool returning metadata and read commands, then a virtual file system tool processing shell commands for specific document sections.
In practice
- Utilize LanceDB for lightweight, in-container search functionality.
- Configure MCP servers by placing markdown files in a 'documentation' folder.
- Design search tools to provide short summaries and metadata for agents.
Topics
- IBM Bob
- MCP Servers
- AI Agents
- Documentation Management
- Hybrid Search
- Virtual File Systems
- LanceDB
Code references
Best for: AI Engineer, Software Engineer
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Editorial summary, takeaway, and curation by AIssential. Original article published by Niklas Heidloff.