Both are code intelligence MCP servers that index your codebase locally for AI agents. Sverklo combines hybrid search with PR review workflows and persistent memory. codebase-memory-mcp is a single C binary that builds a knowledge graph with sub-millisecond query speed across 66 languages. This page is an honest comparison to help you pick the right tool for your project.
| Sverklo | codebase-memory-mcp | |
|---|---|---|
| License | MIT Free for all use | MIT Free for all use |
| GitHub stars | Growing | 1.6k |
| Install | npm install (Node.js, pure JS, no native bindings) | Single C binary (no runtime dependencies) |
| Search | Hybrid BM25 + vector embeddings + PageRank scoring | Knowledge graph queries, sub-ms response time |
| Memory system | Git-pinned (memories tied to SHA, staleness detection) | Knowledge graph acts as persistent memory |
| PR review | Diff-aware with risk scoring and CI gate (--fail-on) | Not included |
| Blast-radius analysis | Yes (trace impact of changes through dependency graph) | Not included |
| Languages | 10 via tree-sitter | 66 via tree-sitter (C parser) |
| Indexing speed | Incremental reindex with live file watching | Linux kernel in ~3 minutes |
| Web dashboard | Yes | No |
| GitHub Action | Yes (open-source) | No |
| Runtime | Node.js | None (static C binary) |
Sverklo uses SQLite with a hybrid retrieval pipeline (BM25 + ONNX embeddings + PageRank graph centrality). It includes diff-aware PR review, git-pinned memory, and a web dashboard. The trade-off: it requires Node.js and currently supports 10 languages.
codebase-memory-mcp uses a single C binary that builds a knowledge graph from your codebase using tree-sitter parsing across 66 languages. Its focus is speed and simplicity: no runtime dependencies, sub-millisecond queries, and the ability to index massive codebases like the Linux kernel in minutes. The trade-off: no PR review, no git-aware memory, and no web interface.
MIT licensed. One command. Works with every MCP client.
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