Claude/add key features docs jl dvc#2540
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mrenee1 wants to merge 2 commits intomodelcontextprotocol:mainfrom
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Claude/add key features docs jl dvc#2540mrenee1 wants to merge 2 commits intomodelcontextprotocol:mainfrom
mrenee1 wants to merge 2 commits intomodelcontextprotocol:mainfrom
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…and visualizations Implements three key features for building research agent workflows on top of the MCP Python SDK: 1. Collaborative Planning: the `research` tool accepts `collaborative_planning=True`. Before executing any work, the agent drafts a research plan via LLM sampling and presents it to the user through the existing elicitation mechanism. Research only proceeds after explicit approval. 2. MCP Support: the server connects to remote MCP servers at startup (configured via the `MCP_SERVERS` JSON env var). Tools from all connected servers are aggregated through `ClientSessionGroup` and their outputs are incorporated into the research context. A companion `list_mcp_tools` tool exposes what is available. 3. Visualizations: when `visualization="auto"` is set, the agent extracts labelled numeric metrics from the research summary (e.g. "Market size: $4.5B") and returns a pure-Python SVG bar chart as a base64-encoded `ImageContent` block — no external charting library required. Also adds docs/research-agent.md documenting all three features with usage examples, configuration instructions, and an architecture overview. https://claude.ai/code/session_01Dm5TVRPucJPKTThQsBycjK
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