Driflyte MCP Server

The Driflyte MCP Server turns a vast, ever‑growing web presence into a structured knowledge base that AI assistants can query in real time. It solves the problem of “how do we give an assistant access to up‑to‑date, topic‑specific information from the web and other digital repositories?” By recursively crawling URLs and indexing the content, Driflyte creates a searchable corpus that is automatically tagged with topics. This allows an assistant to retrieve the most relevant documents for a user’s query, providing richer and more accurate answers than generic web search alone.

At its core, the server offers a set of tools that expose three key capabilities: web crawling, GitHub integration, and topic‑aware retrieval. The crawler follows links from seed URLs, fetching pages, parsing their text, and storing them in a structured index. For GitHub, the server can harvest repository files, issues, and discussions, turning codebases and community conversations into searchable artifacts. Each document is annotated with one or more topics—derived from content analysis or user‑defined tags—which enables fine‑grained, topic‑specific queries. When an assistant requests a document on “natural language processing,” the server returns only those items tagged with that topic, dramatically reducing noise.

The MCP Server is engineered for Retrieval‑Augmented Generation (RAG). It supplies assistants with high‑quality, contextually relevant passages that can be fed directly into the generation pipeline. Because the server itself is built with RAG in mind, it optimizes retrieval latency and relevance scoring, ensuring that assistants can incorporate the latest information without manual intervention. Moreover, Driflyte is an AI‑native component: its indexing and topic modeling processes are continually refined by AI models, making the system self‑improving over time.

Typical use cases include:

• Enterprise knowledge bases – pull documentation, ticket threads, and internal wikis into a single searchable layer.
• Developer assistance – retrieve code snippets, issue discussions, or best‑practice guides from GitHub during coding sessions.
• Research support – aggregate scholarly articles, blog posts, and forum discussions on a specific topic for deep‑research workflows.
• Customer support – index product manuals, FAQs, and community forums so agents can quickly fetch the most relevant help articles.

Integration is straightforward for developers familiar with MCP. The server exposes a standard MCP endpoint that can be added to any client—VS Code, Claude, Cursor, or ChatGPT’s developer mode—using a simple configuration. Once connected, the assistant can invoke tools like , , or to fetch data on demand. The server’s rate limits (100 requests per 5 minutes per IP) ensure fair usage while allowing rapid prototyping and experimentation.

What sets Driflyte apart is its combination of deep, recursive crawling, topic‑aware indexing, and AI‑driven refinement wrapped in an MCP‑compatible interface. It transforms disparate web resources into a unified, searchable knowledge graph that AI assistants can leverage instantly—making it an indispensable bridge between the chaotic world of online information and structured, context‑aware AI reasoning.