Deep Research
This MCP server implementation provides a deep research capability using multiple AI agents. Developed by JoshuaLelon, it offers a tool for conducting in-depth investigations on given queries with customizable research tones. The server is built using Python and integrates with the FastMCP framework and gpt-researcher library. It focuses on progress reporting and error handling, making it suitable for AI applications that require thorough, multi-agent research on complex topics. The implementation is particularly useful for generating comprehensive reports on a wide range of subjects, with the flexibility to adjust the research tone from objective to critical, optimistic, balanced, or skeptical.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- ai-ml
- Source
- PulseMCP
- Repository
- github.com/joshualelon/deep-research-mcp
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve Deep Research from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.