Tentra — Memory for AI Coding Agents

io.github.rdanieli由 GitHub 帳號 rdanieli 發布v1.3.2更新於 Oct 24, 2026

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

發布方自己的服務:Memory.fit

概覽

AI 產生的概覽

Tentra 為 AI 程式助理提供持久化的程式碼圖譜與架構工作區,讓助理查詢符號、呼叫端與設計,而不必反覆讀取原始碼。

可以做什麼
查詢已索引的程式碼圖譜:模糊符號搜尋、呼叫端查找、重新命名修補方案、鄰居走訪、相似程式碼、god node、熱點與快照差異,以及儲存庫導覽與程式碼路徑說明。索引儲存庫並記錄語意標註、嵌入向量與索引工作狀態。設計、讀取、更新、檢查、同步與匯出架構到多種框架,並建立流程視覺化。保存補充資訊:服務對應、領域、API 契約、架構決策記錄與歸屬資訊。
適用情境
適合助理長期在同一儲存庫中工作,需要回答某功能在哪裡實作、誰呼叫了某個符號、架構圖是否仍與程式碼一致等問題。也適合希望在使用 Cursor、Claude Code、Codex 或 Windsurf 等程式助理時同時取得架構圖、ADR 與重構安全檢查的團隊。
執行需求
使用託管的 SSE 端點,或以 npx 執行本機 npm 套件 tentra-mcp(需要 Node.js)。需要託管服務的帳號;預設透過 GitHub 裝置流程驗證,也可用 TENTRA_API_KEY 作為 key 參數或命令列參數傳入。掃描本機程式碼庫需要本機安裝。需要連線至託管 API 的網路。
安裝前請注意
伺服器會把儲存庫資料(包括索引的程式碼與助理產生的標註)傳送到託管的 Tentra 服務。透過 GitHub 裝置流程登入後,憑證會存放在磁碟上。init 指令會為已安裝的 IDE 寫入 MCP 設定檔,並安裝 git post-commit 鉤子,在每次提交後於背景重新索引。許多工具會寫入或修改已保存的架構、契約、決策與對應。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Tentra — Memory for AI Coding Agents,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 SSE。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.rdanieli%2Ftentra/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "tentra-memory-for-ai-coding-agents": {
      "type": "sse",
      "url": "https://trytentra.com/api/mcp"
    }
  }
}

README

tentra-mcp

[npm version] [npm downloads] [CI] [License: MIT]

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-reponpx 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):

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:

"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.

bash
npm install --legacy-peer-depsnpm run build      # tsc --noEmit + esbuild bundle → dist/index.jsnpm start          # run the bundled servernpm test           # vitest

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

License

MIT

來源:README.md,提交 116cf71

工具

0
SourceWeft 尚未讀取此伺服器的工具。

版本歷史

1
  1. v1.3.2最新Sep 16, 2026

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