io.github.rdanieli/tentra (MCP Server)

The io.github.rdanieli/tentra MCP server provides “Memory for AI coding agents.” It focuses on persistent code context via a code graph, including call-graph information, and aims at refactor safety. It is MCP-native and intended to work in tools including Cursor, Claude Code, Codex, and Winds.

🛠️ Key Features

Memory for AI coding agents
Persistent code graph (call graphs)
Refactor safety
MCP-native architecture diagrams (AI-generated)

🚀 Use Cases

Maintaining long-lived software context for coding agents
Supporting code understanding through call graphs
Generating architecture diagrams as part of agent workflows

⚡ Developer Benefits

Persistent code context across agent runs
Token optimization via retained graph/context (topic-listed)
Integration with Cursor, Claude Code, Codex, and Winds

⚠️ Limitations

Scope described as memory/code-graph + refactor safety; no other capabilities are specified beyond 35 MCP tools.

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)

bash

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

One command:

Writes MCP config for Cursor / Claude Code / Codex / Windsurf (whichever are installed)
Installs a git post-commit hook so the code graph auto-refreshes after every commit — no manual re-indexing
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:

code

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)

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
`get_spec_alignment`	Mid-implementation drift check — changed files in, spec context + drift signals out
`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 (13 tools)

Tool	Description
`query_symbols`	Fuzzy trigram search across indexed symbols
`find_references`	Every resolved caller of a symbol — refactor-safety primitive
`safe_rename`	Patch plan (definition + every call site) for renaming a symbol
`explain_codebase`	Agent-ready narrative walkthrough of a whole repo
`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):

json

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

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

json

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

Option 2: Local install (needed for codebase scanning)

bash

npx tentra-mcp

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

Cursor config for local server:

json

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

Claude Code (.mcp.json):

json

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

Usage Examples

Once connected, just talk to your AI:

code

"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.

bash

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

Tentra — Memory for AI Coding Agents

io.github.rdanieli/tentra (MCP Server)

🛠️ Key Features

🚀 Use Cases

⚡ Developer Benefits

⚠️ Limitations

Topics

tentra-mcp

Quick Start (60 seconds)

What is Tentra?

Architecture (10 tools)

Code Graph — Write (4 tools)

Code Graph — Read (13 tools)

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

Setup

Option 1: SSE (zero install)

Option 2: Local install (needed for codebase scanning)

Usage Examples

Export Formats

Links

Development

License

Install

Configuration

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