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Tentra — Memory for AI Coding Agents

Memory for AI coding agents. Persistent code graph + AI architecture diagrams. 32 MCP tools.

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About Tentra — Memory for AI Coding Agents

Tentra — Memory for AI Coding Agents is an MCP server in the Developer Tools category: memory for AI coding agents. Persistent code graph + AI architecture diagrams. 32 MCP tools. It has been installed 0 times through Conduid.

Install

Claude Code
claude mcp add tentra-memory-for-ai-coding-agents -- npx -y tentra-mcp
npx
npx -y tentra-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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README

tentra-mcp

npm version npm downloads CI

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 the persistent memory layer for AI coding agents. 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 32 tools:

Architecture (9 tools)

Tool Description
create_architecture Design a new system from a description
update_architecture Modify an existing architecture
get_architecture Read architecture details
list_architectures Browse all saved designs
analyze_codebase Scan local code and generate diagram
lint_architecture Quality checks (9 rules: orphans, SPOFs, god services)
sync_architecture Detect drift between diagram and code
export_architecture Export to 14 frameworks (Java, Python, Go, Rust, etc.)
create_flow Create step-by-step flow visualization

Code Graph — Write (4 tools)

Tool Description
index_code Walk a repo, Tree-sitter locally, start a semantic indexing job
index_code_continue Resume an in-progress indexing job
record_semantic_node Persist an agent-extracted semantic annotation
get_index_job Check status of an indexing job

Code Graph — Read (10 tools)

Tool Description
query_symbols Fuzzy trigram search across indexed symbols
get_symbol_neighbors BFS traversal in the call/import graph
get_service_code_graph Subgraph for a canvas service
explain_code_path Shortest path between two symbols with semantic context
find_similar_code pgvector cosine ANN over agent-generated embeddings
record_embedding Persist an agent-generated embedding vector
list_god_nodes Highest fan-in/out symbols (architectural smells)
get_quality_hotspots Churn × complexity ranking
list_snapshots Time-travel listing of indexed snapshots
diff_snapshots Files / symbols / god-nodes added/removed between snapshots

Enrichment — Contracts, Decisions, Ownership, Domains (9 tools)

Tool Description
set_service_mapping Link an indexed file or symbol to a canvas service
set_domain_membership Assign a service or file to a domain (bounded context)
record_contract Store a parsed API contract payload (OpenAPI, GraphQL, Protobuf)
bind_contract Link a contract to the symbol that implements it
record_decision Create an Architecture Decision Record, optionally linking code
link_decision Append a link from an ADR to another symbol, file, or service
get_ownership Resolve the owner (team or person) for a file or service
get_decisions_for List ADRs linked to a given entity
get_contracts List 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

Links

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

README mirrored from the source repository 4 months ago. The original is authoritative.

Questions

About Tentra — Memory for AI Coding Agents

How do I install Tentra — Memory for AI Coding Agents?

Run claude mcp add tentra-memory-for-ai-coding-agents -- npx -y tentra-mcp, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is Tentra — Memory for AI Coding Agents safe to use with an AI agent?

Its trust score is 37 out of 100 (low). Conduid hasn't run static security checks on this repository yet, so review the source yourself before granting it credentials. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Tentra — Memory for AI Coding Agents still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.