Budget model + Tessra beats GPT-4 alone. At 15× lower cost.
Tessra indexes your repo into symbols, call graphs, and impact maps — so your AI agent stops reading raw files and starts making real engineering decisions.
Budget model + Tessra outperforms premium. Verified.
Controlled benchmark on a real-world Angular payment component — multiple payment gateways and injected services. Tested across agents (Claude Code, Codex) and model tiers. April 2026.
AI agents are reading code but not understanding it.
Today's coding agents work file-by-file. On a 200K-line repo, that means tokens spent, context lost, and confidence destroyed.
Too many tokens
Agents flood context windows with files they don't need. Cost balloons, signal drops, latency creeps up.
Shallow understanding
Models read snippets but miss relationships. They guess at conventions and invent APIs that don't exist.
Risky refactors
Changing a function feels like a coin flip. No one — human or agent — knows what touches what across the repo.
Slow onboarding
New devs and new agents both spend days learning where things live. Tribal knowledge stays stuck in heads.
From raw repository to impact-aware context.
A local MCP server that indexes your codebase once and answers every agent query with structure, not raw text.
Point Tessra at your repo
One command. Works on any local directory, multi-language, multi-package.
tessra index ./my-repo Your agent queries what it needs
Tessra intercepts every question: returns symbols, callers, impact radius — structured, not raw text.
tessra serve --mcp Ship with confidence
Your agent has the context a senior engineer would have. Impact is known. Risk is surfaced. Changes land clean.
From question to safe change.
Tessra turns a single agent question into a confident engineering decision — impact, risk, and the path forward, before a line of code changes. The agent gets the result, not the graph.
This structure is computed internally — your agent receives only what matters.
This change touches billing, checkout, and the Stripe webhookhandler. Refactor should preserve the existing webhook payload structure — downstream consumers depend on field order and types.
Senior engineering judgment, served as context.
Tessra doesn't replace your agent — it gives it the same situational awareness a senior engineer would have on day 800 of the project.
Ship AI changes without breaking prod
Every refactor comes with an impact radius. Know what breaks before you push — across files, services, and tests.
Spend 15× less on tokens
Tessra returns only what the agent needs: symbols, signatures, related callers. Stop paying to re-parse the same files.
Your code never leaves your machine
Indexes run locally. No cloud. No uploads. No external APIs. MCP-native — plugs into any compatible agent.
Built for stacks teams actually ship
First-class indexers for real production codebases — not toy examples.
Your code never leaves your machine.
Tessra runs locally. No uploads. No cloud indexing. No external processing. Your code stays where it belongs.
- Runs on your machine
- MCP-native local server
- No data sent to external APIs
- Works with your existing agents
Simple, honest pricing.
Start free. Upgrade when you're shipping with agents every day.
For developers exploring AI-assisted development.
- 1 repository
- Symbol search & smart context
- 50 queries / day
- Django · Angular · Flutter
- Community support
For developers shipping with agents every day.
- Unlimited repositories
- All 15 MCP tools
- Impact radius & call graph
- Multi-repo workspace
- Angular · Django · Flutter
- More stacks coming soon
- Email support
For teams shipping production AI systems.
- Everything in Pro
- Team licenses
- Dedicated support + SLA
- Custom integrations
- Annual billing
- Compliance & audit logs
Join the early access program.
First teams get lifetime discounted pricing at GA. Limited spots.
No spam. No credit card required.
Used by developers shipping AI-assisted changes in production.
"Tessra made our Angular codebase approachable for Claude. The impact radius alone saved us from two bad refactors."
"We switched from GPT-4 to Haiku + Tessra. Same quality, drastically lower cost."