tempograph

Your AI agent finds the right files. Every time.

One MCP tool call gives your coding agent the exact files it needs before making changes. No guessing. No irrelevant context.

$pip install tempograph

The problem

Agents guess which files to look at
They search by filename and grep for keywords
They miss critical dependencies
They break things downstream
They waste tokens on irrelevant code

The fix

Tempograph builds a real dependency graph
Agent calls prepare_context
Gets the exact files that matter
Based on structural analysis, not text matching
Knows when to skip context (adaptive gating)

+27%

Better file selection (GPT-4o)

21ms

Warm query time

p=0.049

Statistically significant

How it works

your repo ──> tree-sitter parse ──> symbols + edges ──> SQLite graph

    Agent calls prepare_context(task="fix auth bug")

    ──> keyword extraction ──> symbol search ──> graph traversal

    <── KEY FILES + callers + callees + risk signals

When your agent needs more

"What breaks?"

Before changing a file, see every importer and caller that could break.

blast_radius

"Show me everything"

Focus on a symbol and see callers, callees, and related files in context.

focus

"What's risky?"

Find files where complexity, coupling, and size overlap. Change carefully.

hotspots

"What's dead?"

Find exported symbols with zero incoming references. Safe to delete.

dead_code

"What changed?"

Impact analysis of your current diff — breaking-change risk signals.

diff_context

"Orient me"

New to a codebase? Get size, languages, entry points, key files.

overview

Set up in 30 seconds

Add to your MCP config (Claude Code, Cursor, Windsurf, or any MCP client):

{
  "mcpServers": {
    "tempograph": {
      "command": "tempograph-server",
      "args": []
    }
  }
}

Give your agent better context

Install tempograph and stop guessing which files matter.

View on GitHub PyPI