Open-source Deep Research

Deep Research for FastAgent

Give FastAgent workflows a cited research capability that fits MCP-first agent design.

MCP-first setup feels natural

FastAgent workflows already treat MCP as a core integration path. AutoSearch follows that shape by exposing research tools over MCP, so agents can request source discovery without custom scraping code or a host-specific integration.

Good fit for agent experiments

FastAgent users often prototype agent behavior quickly. AutoSearch gives those prototypes access to real evidence from 40 channels, helping teams test research prompts, tool policies, and citation expectations with less custom plumbing.

Chinese sources included early

When agent experiments target global products or technical communities, English-only sources miss important signals. AutoSearch includes 10+ Chinese sources, letting FastAgent workflows compare regional discussions alongside GitHub, arXiv, and developer forums.

How it fits

AutoSearch runs as an MCP-native research server that FastAgent can call when a workflow needs outside evidence. FastAgent keeps the agent definitions, routing, and model choices. AutoSearch performs open-source deep research across technical, academic, social, and Chinese channels, then returns cited results for the agent to summarize or act on. This keeps experiments lightweight while still grounding decisions in current sources.

Try this prompt

Research recent MCP server patterns for FastAgent workflows.
Return setup examples, failure modes, and citations from docs and GitHub.