{"id":"vectorcode","name":"VectorCode","homepage":"https://github.com/Davidyz/VectorCode","repo_url":"https://github.com/Davidyz/VectorCode","category":"developer-tools","subcategories":["code-intelligence","rag","neovim","mcp"],"tags":["code-indexing","vector-search","chromadb","neovim","mcp","rag","tree-sitter","python","open-source"],"what_it_does":"VectorCode is a code repository indexing tool that uses tree-sitter semantic chunking and Chroma vector embeddings to inject task-relevant codebase context into LLM prompts, reducing hallucination on proprietary or niche codebases. It provides a CLI, Neovim Lua API, and MCP server.","use_cases":["Indexing a private or niche codebase so LLMs have accurate context when answering questions about it","Building Neovim AI plugins that retrieve semantically relevant code chunks before querying an LLM","Providing MCP-connected agents with precise code search and retrieval over large repositories"],"not_for":["Teams using IDEs other than Neovim (primary integration is Neovim; MCP is secondary)","Use cases requiring cloud-hosted vector search (Chroma runs locally)","Simple projects where the LLM's built-in context window is sufficient"],"best_when":"You are a Neovim user with a large or non-public codebase where LLMs frequently hallucinate, and you want semantic code retrieval integrated into your editor's AI workflow.","avoid_when":"You need a GUI-based or IDE-agnostic solution — the primary UX is Neovim-centric.","alternatives":["codebase-mcp","greptile","sourcegraph-cody"],"af_score":77.0,"security_score":70.0,"reliability_score":null,"package_type":"mcp_server","discovery_source":["github"],"priority":"low","status":"evaluated","version_evaluated":"0.7.20","last_evaluated":"2026-03-01T09:50:06.355810+00:00","performance":{"latency_p50_ms":null,"latency_p99_ms":null,"uptime_sla_percent":null,"rate_limits":null,"data_source":"llm_estimated","measured_on":null}}