Model Context Protocol Server

The Mcp Docs Assistant is a Model Context Protocol (MCP) server built on Claude’s MCP SDK that bridges the gap between static documentation and dynamic AI interaction. In many development environments, documentation lives in read‑only files or web pages that are difficult for AI assistants to parse and act upon. This server transforms those resources into interactive, queryable assets that an AI can consult in real time, enabling developers to ask precise questions about code samples, API contracts, or architectural decisions without leaving their workflow.

At its core, the server exposes a set of MCP resources that map directly to documentation artifacts—Markdown files, JSON schemas, and even PDF extracts. Each resource is annotated with metadata such as version, author, and relevance tags, allowing the AI to prioritize recent or critical sections. The server also provides a prompt endpoint that injects contextual snippets into the assistant’s prompt, ensuring that answers are grounded in the most relevant documentation. By handling resource retrieval and context injection internally, the server eliminates latency that would otherwise arise from external HTTP calls or file system lookups.

Key capabilities include:

• Dynamic Context Injection – The server automatically extracts the most pertinent sections of a document based on the user’s query and supplies them as part of the prompt, keeping responses accurate and up‑to‑date.
• Fine‑grained Access Control – Resources can be tagged with access levels, allowing teams to restrict sensitive documentation while still enabling AI assistance for public APIs.
• Sampling and Temperature Management – The server offers adjustable sampling controls, giving developers the ability to fine‑tune the creativity of responses without modifying the AI model itself.
• Rich Metadata Handling – Each resource carries metadata that can be queried programmatically, enabling advanced search and filtering directly within the AI interface.

Real‑world scenarios that benefit from this MCP server include:

• Onboarding New Engineers – Instead of sifting through a sprawling docs repo, new hires can ask the AI for “how to use the authentication endpoint” and receive a concise, code‑ready answer.
• Continuous Integration Pipelines – CI tools can query the server for policy documents or compliance guidelines, ensuring that generated code adheres to organizational standards.
• Knowledge Base Expansion – Teams can continuously add new documentation, and the server automatically makes it discoverable by the AI without any redeployment.

Integration is straightforward for developers familiar with MCP: the server registers its resources and tools during startup, and any Claude‑compatible client can send a resource request or prompt request to retrieve context. Because the server handles all protocol details, developers can focus on maintaining high‑quality documentation rather than building custom adapters.

In summary, the Mcp Docs Assistant turns static documentation into a living knowledge base that AI assistants can interrogate instantly. By automating context injection, enforcing access controls, and providing fine‑grained sampling options, it empowers teams to embed expert guidance directly into their development workflows, reducing friction and accelerating productivity.