Implement v0.1: agentic RAG mesh (LangGraph agent + MCP retrieval server + FAISS) - #1
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Single LangGraph agent talks to a real MCP tool server over streamable-http, backed by a local FAISS vector store built over the repo's own docs. Config-driven LLM provider swap (Anthropic/OpenAI/ Bedrock) via init_chat_model. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Hermetic unit suite (fake embeddings/chat model, in-memory MCP session) needs no network or API key. Integration tier actually runs docker compose and hits /chat, opt-in only (needs a live LLM key). CI runs ruff, mypy, and the unit suite on every push/PR. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
mcp-server builds the FAISS index at image build time and serves it over streamable-http, internal-only. agent-api depends on its healthcheck and exposes POST /chat on host port 8080. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
project-docs/ holds the public architecture record: three ADRs for the closest judgment calls, the fuller rationale doc, and an end-to-end developer guide. README gets a Mermaid architecture diagram, quickstart, and CI badge. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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Summary
Test plan