Open-source Deep Research

Searching Twitter from your AI Agent

Use fast-moving Twitter discussion as cited context inside broader research tasks.

Real-time discourse for agents

Twitter can surface launches, complaints, expert takes, and early adoption signals quickly. AutoSearch lets agents include that discussion in a research prompt and cite the posts that support each trend or claim.

Compared with slower sources

Fast social signals need grounding. AutoSearch can compare Twitter findings with GitHub, docs, papers, Reddit, Hacker News, YouTube, and Chinese channels, helping agents decide which signals deserve confidence.

Promptable monitoring workflows

Through MCP, an agent can ask AutoSearch to monitor Twitter for a topic, competitor, or incident and return cited summaries. The same prompt can include other channels for a more complete research packet.

How it fits

AutoSearch puts Twitter into an agent's cited research loop. The agent asks a question, AutoSearch gathers relevant posts and surrounding evidence from 40 channels, and the agent summarizes patterns, disagreements, and risks. This is useful for launch analysis, market monitoring, incident response, and developer sentiment research where speed matters but source comparison is still necessary.

Try this prompt

Search Twitter for current discussion about MCP adoption.
Compare cited posts with GitHub issues, docs, and Hacker News threads.