Tentra
Tentra gives your AI coding agent memory. The code-graph indexer walks your repository with Tree-sitter locally, extracts symbols and call edges, and stores them in a persistent
queryable graph. On the tentra monorepo we measured 99.4% token reduction (156.8× ratio) across 8 "where is X implemented?" queries — 114,644 tokens via file re-read vs 731 tokens via
graph query. Uses the "agent-as-LLM" pattern — the Claude/Cursor/Codex agent you already have does the semantic extraction, so there is zero LLM cost on Tentra's side and no API key
setup for end users. Also includes an architecture workspace with 9 MCP tools for diagrams and 14-framework code export.
Overview
Tentra — Memory for AI Coding Agents
Tentra is the persistent memory layer for AI coding agents. Two pillars:
- Code graph — Index your repo once. Agents query a structured graph of files, symbols, imports, and call edges instead of re-grepping source every session.
- Architecture workspace — Describe a system in natural language, get an interactive diagram and production-ready code in 14 frameworks.
Why it saves tokens
Dogfood benchmark on the Tentra monorepo:
- 99.4% token reduction (156.8× ratio) across 8 "where is X implemented?" queries
- 114,644 tokens via file re-read → 731 tokens via graph query
- Zero LLM cost on Tentra's infra (agent-as-LLM pattern: your Claude/Cursor/Codex agent does the semantic extraction)
- Zero API key setup on your side
Setup
Option 1: SSE (zero install)
Cursor / Claude Code / Codex / Windsurf — add to your MCP config:
```json { "mcpServers": { "tentra": { "type": "sse", "url": "https://trytentra.com/api/mcp?key=YOUR_API_KEY" } } } ```
Get your API key at https://trytentra.com/settings after a one-click GitHub sign-in.
Option 2: Local (stdio)
```bash npx -y tentra-mcp ```
Authenticates via GitHub on first use. Needed for local codebase scanning.
32 MCP Tools
- Architecture (9):
create_architecture,update_architecture,get_architecture,list_architectures,analyze_codebase,lint_architecture,sync_architecture,export_architecture,create_flow - Code Graph — Write (4):
index_code,index_code_continue,record_semantic_node,get_index_job - Code Graph — Read (10):
query_symbols,get_symbol_neighbors,get_service_code_graph,explain_code_path,find_similar_code,record_embedding,list_god_nodes,get_quality_hotspots,list_snapshots,diff_snapshots - Enrichment (9):
set_service_mapping,set_domain_membership,record_contract,bind_contract,record_decision,link_decision,get_ownership,get_decisions_for,get_contracts
Links
- Website: https://trytentra.com
- Docs: https://trytentra.com/docs
- GitHub: https://github.com/rdanieli/archbuilder
- npm: https://www.npmjs.com/package/tentra-mcp
What agents use it for
- "Where is auth handled?" →
query_symbols→ file paths + line ranges in one call - "What calls this function?" →
get_symbol_neighbors→ BFS through the call graph - "Why was this service split?" →
get_decisions_for→ linked ADRs - "Who owns this file?" →
get_ownership→ team / person - "Find code similar to this snippet" →
find_similar_code→ pgvector cosine ANN
Server Config
{
"mcpServers": {
"tentra": {
"type": "sse",
"url": "https://trytentra.com/api/mcp?key=YOUR_API_KEY"
}
}
}Project Info
Created At
2 months agoUpdated At
2 months agoAuthor Name
rdanieliStar
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