Kivgraph MCP server

Kivgraph

Kivgraph is a local cross-repository code intelligence MCP server for AI coding agents. It builds a canonical semantic code graph across multiple registered repositories and answers questions about symbols, repository relationships, callers, dependencies and change impact.

https://github.com/user-attachments/assets/b8410905-323d-4caf-9d7b-57c50ffca48c

kivgraph ui — read-only 3D view of the published graph.

It indexes a corpus once and serves an immutable graph: the edges are resolved by go/types, the TypeScript checker and rust-analyzer, not by matching names. That is the difference from a search tool, and it is what makes an empty answer worth something — an empty reference list means nobody calls it, not that nothing was found, and grep cannot tell those apart.

Kivgraph is focused on semantic code relationships, not automatic discovery of every HTTP, gRPC, Kafka or database runtime flow between services.

Documentation

Read the Kivgraph user documentation for installation, MCP clients, code intelligence, repository relationships and workspace code graphs. The same pages are the source of landing/src/content/docs in this checkout, which is what a reader on a fork or without a network still has.

What each tool answers

Thirteen read-only tools, plus two consent-gated mutations (indexproject and startindex_project) that a client has to authorize before either can register a repository or publish a generation.

Every row that names a symbol carries its repository, path, qualified name and line range, so it can be opened without a second call, and every tool accepts that triple in place of an opaque key.

Where it loses. A rare name in one small repository is cheaper with grep, and indexing a small file costs more than reading it. It wins on common names, on transitive impact, on consumers in another repository, and on proving an absence. Measured over 29 questions against a 37-repository corpus (benchmarks/graph-tools-comparison/results-all.json, commit 954b9eb, tokenizer o200kbase): 35,961 tokens for Kivgraph against 267,980 for grep plus reading, both exact on 28 of the 29, median 5.95x per question in Kivgraph's favour. grep is cheaper on 5 of those 29, all of them at full recall on both sides: T1go_trivial asks for a name the corpus declares twice, and there grep costs 0.53x what Kivgraph does.

A second harness, benchmarks/mcp-token-cost, compares against the host's own tool output captured verbatim, but it runs on Kivgraph's own single repository of 13,222 symbols: 7.64x on the answers themselves and 1.60x over a whole session, against a 2.41x floor set by the source bodies both arms pay for.

Status

Released and in use. kivgraph version reports the published release; the backlog and the acceptance gate of every phase are in TASKS.md.

Shortened. The full README is on GitHub.