Tentra — Memory for AI Coding Agents

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Memory for AI coding agents. Call graphs + refactor safety + persistent code context. 35 MCP tools.

Installation

Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).

Remote (sse)
Claude Code
claude mcp add --transport sse tentra-memory-for-ai-coding-agents 'https://trytentra.com/api/mcp'
Configuration JSON (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "tentra-memory-for-ai-coding-agents": {
            "type": "sse",
            "url": "https://trytentra.com/api/mcp"
        }
    }
}
NPM package tentra-mcp
Claude Code
claude mcp add tentra-memory-for-ai-coding-agents -e 'TENTRA_API_KEY=<your tentra_api_key>' -- npx -y tentra-mcp@1.3.2
Configuration JSON (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "tentra-memory-for-ai-coding-agents": {
            "command": "npx",
            "args": [
                "-y",
                "tentra-mcp@1.3.2"
            ],
            "env": {
                "TENTRA_API_KEY": "<your tentra_api_key>"
            }
        }
    }
}

Variables d'environnement

  • TENTRA_API_KEY secret Tentra API key (optional — device flow auth via GitHub is used by default)

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. tentra-mcp
  2. Quick Start (60 seconds)
  3. What is Tentra?
  4. Setup
  5. Usage Examples
  6. Export Formats
  7. Links
  8. Development
  9. License

tentra-mcp

Memory for AI coding agents. Persistent code graph + AI-generated architecture diagrams — MCP-native. Works in Cursor, Claude Code, Codex, and Windsurf.

Dogfood benchmark on our own monorepo: 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 query_symbols. Full write-up →

Quick Start (60 seconds)

cd your-repo
npx tentra-mcp init --hook

One command:

  1. Writes MCP config for Cursor / Claude Code / Codex / Windsurf (whichever are installed)
  2. Installs a git post-commit hook so the code graph auto-refreshes after every commit — no manual re-indexing
  3. Auto-derives your repo_id from the git remote and saves it to .tentra/metadata.json

Then grab your API key at trytentra.com/settings, replace YOUR_TENTRA_API_KEY in the generated config, reload your IDE, and ask your agent:

Index this codebase with Tentra and list the god-nodes

From here on, every git commit fires a background re-index. Your agents stay caught up automatically.

Skip the hook: drop --hook — just writes IDE configs. Manual stdio install: npx tentra-mcp (opens browser for GitHub device-flow auth on first tool call). API key instead: npx tentra-mcp --key YOUR_API_KEY.

What is Tentra?

Tentra is an AI-native architecture platform for engineering teams. Describe a system — get a diagram and 14-framework code exports. Index your repo — agents query a structured graph of files, symbols, imports, and call edges instead of re-grepping source every session.

This MCP server gives your AI assistant 36 tools:

Architecture (10 tools)
ToolDescription
create_architectureDesign a new system from a description
update_architectureModify an existing architecture
get_architectureRead architecture details
list_architecturesBrowse all saved designs
analyze_codebaseScan local code and generate diagram
lint_architectureQuality checks (9 rules: orphans, SPOFs, god services)
sync_architectureDetect drift between diagram and code
get_spec_alignmentMid-implementation drift check — changed files in, spec context + drift signals out
export_architectureExport to 14 frameworks (Java, Python, Go, Rust, etc.)
create_flowCreate step-by-step flow visualization
Code Graph — Write (4 tools)
ToolDescription
index_codeWalk a repo, Tree-sitter locally, start a semantic indexing job
index_code_continueResume an in-progress indexing job
record_semantic_nodePersist an agent-extracted semantic annotation
get_index_jobCheck status of an indexing job
Code Graph — Read (13 tools)
ToolDescription
query_symbolsFuzzy trigram search across indexed symbols
find_referencesEvery resolved caller of a symbol — refactor-safety primitive
safe_renamePatch plan (definition + every call site) for renaming a symbol
explain_codebaseAgent-ready narrative walkthrough of a whole repo
get_symbol_neighborsBFS traversal in the call/import graph
get_service_code_graphSubgraph for a canvas service
explain_code_pathShortest path between two symbols with semantic context
find_similar_codepgvector cosine ANN over agent-generated embeddings
record_embeddingPersist an agent-generated embedding vector
list_god_nodesHighest fan-in/out symbols (architectural smells)
get_quality_hotspotsChurn × complexity ranking
list_snapshotsTime-travel listing of indexed snapshots
diff_snapshotsFiles / symbols / god-nodes added/removed between snapshots
Enrichment — Contracts, Decisions, Ownership, Domains (9 tools)
ToolDescription
set_service_mappingLink an indexed file or symbol to a canvas service
set_domain_membershipAssign a service or file to a domain (bounded context)
record_contractStore a parsed API contract payload (OpenAPI, GraphQL, Protobuf)
bind_contractLink a contract to the symbol that implements it
record_decisionCreate an Architecture Decision Record, optionally linking code
link_decisionAppend a link from an ADR to another symbol, file, or service
get_ownershipResolve the owner (team or person) for a file or service
get_decisions_forList ADRs linked to a given entity
get_contractsList contracts, optionally filtered by kind or service

Setup

Option 1: SSE (zero install)

Add to your IDE's MCP config — no local install needed:

Cursor (Settings > Features > MCP > Add Server):

{
  "tentra": {
    "type": "sse",
    "url": "https://trytentra.com/api/mcp?key=YOUR_API_KEY"
  }
}

Claude Code (.mcp.json in project root):

{
  "mcpServers": {
    "tentra": {
      "type": "sse",
      "url": "https://trytentra.com/api/mcp?key=YOUR_API_KEY"
    }
  }
}
Option 2: Local install (needed for codebase scanning)
npx tentra-mcp

Authenticates automatically via GitHub on first use. Credentials are saved to ~/.tentra/credentials.

Cursor config for local server:

{
  "tentra": {
    "command": "npx",
    "args": ["tentra-mcp"]
  }
}

Claude Code (.mcp.json):

{
  "mcpServers": {
    "tentra": {
      "command": "npx",
      "args": ["tentra-mcp"]
    }
  }
}

Usage Examples

Once connected, just talk to your AI:

"Design a payment system with Stripe, Kafka, and PostgreSQL"
→ AI calls create_architecture → diagram at trytentra.com/arch/xxx

"Scan this codebase and generate the architecture"
→ AI calls analyze_codebase → detects services, DBs, queues

"Export this architecture to Java Spring Boot"
→ AI calls export_architecture → downloads zip with project scaffold

"What changed since last time? Is my diagram outdated?"
→ AI calls sync_architecture → drift report with accuracy score

Export Formats

Java (Spring Boot), Node.js (Fastify), Python (FastAPI), Go (chi), Rust (Axum), .NET (ASP.NET), Kotlin (Ktor), PHP (Laravel), Ruby (Rails), Elixir (Phoenix), Docker Compose, Mermaid, ADR, Terraform

Development

This repo contains the open-source MCP server. The Tentra API and web app are a separate hosted service at trytentra.com.

npm install --legacy-peer-deps
npm run build      # tsc --noEmit + esbuild bundle → dist/index.js
npm start          # run the bundled server
npm test           # vitest

The published npm package (tentra-mcp) ships only the bundled dist/ — source is here for auditability and community contributions.

License

MIT

Questions fréquentes

Qu'est-ce que Tentra — Memory for AI Coding Agents ?

Memory for AI coding agents. Call graphs + refactor safety + persistent code context. 35 MCP tools.

Comment installer Tentra — Memory for AI Coding Agents ?

Il fonctionne comme serveur distant. Dans Claude Code : claude mcp add --transport sse tentra-memory-for-ai-coding-agents 'https://trytentra.com/api/mcp'. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.

Faut-il une clé API pour Tentra — Memory for AI Coding Agents ?

Oui. Il attend TENTRA_API_KEY, à renseigner dans sa configuration.

Tentra — Memory for AI Coding Agents est-il open source ?

Oui. Son code est sur GitHub sous licence MIT.

Qui maintient Tentra — Memory for AI Coding Agents ?

Il est publié par rdanieli. AI.tn le référence sans le maintenir ni le recommander.

Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.