Novgraph
OfficialConfigures Novgraph as an MCP server for Codeium's Windsurf editor via mcp_config.json, plus an AGENTS.md instruction pointer and a /novgraph workflow, giving the agent graph-backed answers about files, symbols, history and impact.
Sets up Novgraph for GitHub Copilot by writing the MCP server registration into VS Code's mcp.json, adding instructions to .github/copilot-instructions.md, and installing a /novgraph prompt so Copilot can query the codebase knowledge graph.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Novgraphwhat's the blast radius of changing src/auth.py?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
novgraph
A live knowledge graph of your codebase, queried by coding agents.
Command-line client for Novgraph, a hosted knowledge graph of a git repository. The graph holds your files and symbols as nodes and their real relationships as typed edges, and coding agents query it over MCP or the shell for four things a file read cannot give them: the recorded intent behind each commit, files that change together without importing each other, ranked blast radius, and computed architecture.
Token savings: 78% to 99.74% per answer, measured against the cost of reading the files each answer cites — not modelled, not estimated from a benchmark.
This repository is the client only — auth, agent detection, MCP registration and request transport. Python 3.11+, standard library, no dependencies, no engine. Indexing, storage and retrieval run on Novaya's servers.
uv tool install novaya # the PyPI package is `novaya`
novgraph install <KEY> # generate a key at https://app.trynovaya.cominstall detects every supported agent on the machine, registers the MCP
server, writes a pointer into each agent's instruction file, adds a
/novgraph command, resolves which indexed codebase this checkout is, and
verifies each step. novgraph doctor re-runs those checks with an exit code.
What problem it solves
A coding agent starts each session with no memory of the repository. To answer "what does this touch", it greps, opens files, and infers — spending tokens to rebuild a picture it loses at the end of the session. Three classes of fact are not recoverable that way at all:
Fact | Where it lives | Why reading files misses it |
Why a change was made | commit history + recorded reasoning | git stores the diff, not the intent or the rejected alternative |
Files that change together | commit co-occurrence | there is no import, call or reference to follow |
Computed architecture | whole-graph analysis | hubs, layering and cycles are properties of the graph, not of any file |
Novgraph holds all three in a knowledge graph per repository and answers from the graph. A query returns a few hundred tokens where the equivalent file reads cost tens of thousands, and every answer reports the difference measured against the files it cites:
◆ Novgraph · saved you an estimated ~191k tokens · ~622k this session
traced what changes with core/novgraph_summary.py · vs reading the 12 files it citesMeasured range: 78% to 99.74% fewer tokens per answer. The floor is a short answer about a small file — a ~223-token summary against a ~1k file is 78%. The ceiling is a structural answer about a large dependency set — ~500 tokens against the 191k of cited files above is 99.74%. The ratio is a property of how much the answer's cited files would have cost to read, so it is reported per answer rather than claimed as a headline.
Related MCP server: weavatrix-js
What's in the knowledge graph
One graph per repository, built from the working tree and the full git history.
Nodes | files, and symbols within them: |
Structural edges |
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History edges |
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Inferred edges | runtime relationships no parser can see, added by an LLM pass over the graph |
Records | one why-entry per commit: subject, intent, reasoning, files touched, serial number |
Computed views | load-bearing hubs, de-facto subsystems, layering, dependency cycles — derived from the whole graph, not declared anywhere |
Language coverage is Python and JS/TS via tree-sitter, with a generic tree-sitter path for Go, Rust, Java and C. Nothing about the graph is hand-maintained: it is rebuilt from the repository on every push.
Features
Recorded intent per commit.
why <path>returns the reasoning behind the changes that touched a file, written back by agents viarecord-why.Co-change coupling.
connections <path>includes files that historically change with it and have no static link to it, with the commit count.Blast radius, ordered by certainty.
impact <path>separates facts (callers, importers) from history (co-change), and states when the history is too shallow to be evidence.Computed architecture.
overviewreports load-bearing files, de-facto subsystems, layering and dependency cycles.Exact identifier resolution, including module-level constants. A query for
MAX_RETRIESreturns its definition; if nothing is named that, the answer says so instead of returning fuzzy matches on a fragment of the name.History follows renames. After
git mv, recorded reasoning and co-change edges move to the new path instead of staying attached to a path that no longer exists.Savings measured, not modelled. Every answer is compared against the token cost of reading the files it cites — 78%–99.74% in measured sessions. An answer whose baseline cannot be established reports no saving rather than a guess.
/novgraph savingsprints the per-query ledger.Per-session deduplication. A repeated query in one agent session returns a short reference instead of the same text again.
Explicit staleness. While a new commit is indexing, changed files are flagged and ranked below fresh ones, and structural answers name the commit they describe. Anything newer than the index is reported as such, so the agent reads the working tree instead.
Knowledge graph vs. the alternatives
grep + file reads | static code graph | novgraph | |
Symbols, calls, imports | manual | yes | yes |
Commit intent | no | no | yes |
Co-change without a static link | no | no | yes |
Blast radius split facts/history | no | partial | yes |
Constants resolved exactly | yes | partial | yes |
History survives a rename | n/a | no | yes |
Refresh | none needed | re-run it | webhook per push |
Token cost reported | no | no | per answer, 78%–99.74% token savings measured |
Runs on your machine | yes | yes | no |
Commands
Setup
novgraph install <KEY> set up this machine and repository, then verify
novgraph install - read the key from stdin
novgraph doctor re-run every check; non-zero exit on failure
novgraph doctor --json same, machine-readable
novgraph doctor --quick skip the MCP handshake and graph read
novgraph wire <agent> set up one agent (claude-code, codex, cursor, ...)
novgraph adapters list supported agents and what each one needs
novgraph key <KEY> replace this machine's key
novgraph upgrade update the client, then re-sync every bound repo
novgraph uninstall remove every entry and file it wroteQuerying the graph
Each verb works in any terminal inside a bound repository, and is also exposed as an MCP tool to agents.
novgraph summary what this project is
novgraph overview computed architecture
novgraph search <query> locate code by concept or exact name
novgraph why <path> recorded reasoning behind a file
novgraph connections <path> imports, callers, co-change
novgraph impact <path> what breaks, most certain first
novgraph recent [limit] recent commits and their intent
novgraph ask "<question>" a briefing composed from several reads
novgraph record-why "<why>" --intent "..." --reasoning "..." --commit <sha>
novgraph codebases which repositories this key can read
novgraph call <tool> --json '{...}' any tool, including newer than this clientAgent workflows
install writes a /novgraph command into each agent that supports one:
/novgraph review checks the current diff against co-change history
/novgraph brief <task> files, constraints, blast radius, a plan
/novgraph impact <file> what breaks, most certain first
/novgraph debug <error> ranked causes, each with evidence and a check
/novgraph record write a commit's reasoning back to the graph
/novgraph onboard [area] guided tour of an unfamiliar codebase
/novgraph summary the codebase at its latest indexed commit
/novgraph savings measured token savings for this sessionCodex has skills rather than slash commands, so there it is $novgraph.
What it writes
Agent | MCP registration | Instruction file | Command file |
Claude Code |
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Codex |
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Cursor |
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GitHub Copilot | VS Code |
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Gemini CLI |
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Windsurf |
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Cline |
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OpenCode |
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Plus .novgraph/rules.md, .novgraph/skills.md and .novgraph/blueprint.md
in the repository — generated, safe to commit.
Every edit is one named MCP entry and one marked block, added by
read-modify-write. A config file that cannot be parsed is left byte-for-byte
unchanged and reported. novgraph uninstall removes exactly what was written.
Key handling and data
The key is stored in the OS credential store: Windows DPAPI, macOS Keychain, libsecret via
secret-tool, or a0600file. It is never written to the repository, an agent config, or a log.NOVGRAPH_API_KEYoverrides the store when set — for CI.NOVGRAPH_API_BASEoverrides the endpoint.Requests carry the key, the query, and a per-session id. File contents are not sent. The hosted graph holds paths, symbol names, relationships, counts and recorded reasoning.
Indexing reads the repository through your GitHub or GitLab grant on the server side; the client never uploads source.
Requirements
Python 3.11 or newer. No third-party packages.
A repository indexed by Novgraph — connect it at app.trynovaya.com.
For the MCP path, an agent that speaks MCP over stdio. The shell verbs work anywhere.
Development
python -m pytest -q # 80 tests, no network, no dependenciesAdding an agent is one module in novaya/adapters/ plus an entry in
ADAPTERS; there are eight to copy from. See
CONTRIBUTING.md. Report vulnerabilities privately per
SECURITY.md.
License
Apache-2.0 for this client. The hosted service it queries is proprietary.
This server cannot be deployed
Maintenance
Related MCP Connectors
Repository knowledge graph MCP server for codebase understanding and debugging.
Codebase graphs, caller impact analysis, and recorded project context for AI coding agents.
Code intelligence for LLMs. Analyze, search, and retrieve code from any public git repository.
Hosted code graph over MCP: exact callers, dependencies, and cross-repo blast radius for AI agents.
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