Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Governed data discovery, exact queries, decisions, simulations, and runtime utilities over MCP.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
ALGENTA_API_KEY, ALGENTA_BASE_URL, Authorization标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"algenta": {
"command": "uvx",
"args": [
"algenta-mcp"
],
"env": {
"ALGENTA_API_KEY": "your-value",
"ALGENTA_BASE_URL": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add --transport http algenta https://api.algenta.ai/mcp --header 'Authorization: your-value'claude mcp add algenta --env ALGENTA_API_KEY=your-value --env ALGENTA_BASE_URL=your-value -- uvx algenta-mcp运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"algenta": {
"url": "https://api.algenta.ai/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"algenta": {
"command": "uvx",
"args": [
"algenta-mcp"
],
"env": {
"ALGENTA_API_KEY": "your-value",
"ALGENTA_BASE_URL": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"algenta": {
"type": "http",
"url": "https://api.algenta.ai/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"algenta": {
"type": "stdio",
"command": "uvx",
"args": [
"algenta-mcp"
],
"env": {
"ALGENTA_API_KEY": "your-value",
"ALGENTA_BASE_URL": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
你的选择通过 Cookie 保存在这台设备上,无需账户。
ALGENTA_BASE_URL envAuthorization 机密 必填 HTTP header这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 thyn-ai 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:ALGENTA_API_KEY, Authorization
两种方式都可以:安装在你的电脑上,或者连接云端版本。
GitHub 仓库最后更新于–,最新版本(1.0.31)于43天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Spec Driven Development, Remote Desktop Commander, ScienceShot science reference
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Sourced, citable answers in radiation and particle physics, photonics, electronics and quantum.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Python and TypeScript client libraries and the official MCP server for [Algenta](https://algenta.ai) — self-hosted building blocks for AI applications.
📖 Full documentation: [GitHub Wiki](https://github.com/thyn-ai/algenta-sdk/wiki)
Docs · Python SDK · TypeScript SDK · MCP server · Integrations · Examples · Contributing
Custom Mojo kernels give Algenta its speed. Your team never writes a line of Mojo — the blocks speak Python and TypeScript. On your infrastructure, not ours. These SDKs are how Python and TypeScript call the engine: typed access to governed data queries, Monte Carlo simulations and recommendations, decision memory with execution receipts that pin the policy and schema snapshots each execution ran under, agent runs with human-in-the-loop approvals, managed connectors, and a full audit trail — enforced by the engine, never by client-side convention.
MCP server (`algenta-mcp`) — the official MCP server for Algenta lives in THIS repository at packages/mcp/ (implementation: packages/mcp/algenta_mcp; stdio transport by default, Streamable HTTP optional). Install it with pip install algenta-mcp and run it as the algenta-mcp command; it is also on the official MCP Registry as io.github.thyn-ai/algenta. The framework integrations (LangChain, LlamaIndex, Vercel AI SDK, …) are what live in the companion repository thyn-ai/algenta-integrations — not the MCP server.
Introspection (initialize/tools/list) needs no credentials. Executing tools requires a free community login — device registration at algenta.ai (free): run algenta login, or create a key at https://app.algenta.ai/dashboard/api-keys, then set ALGENTA_API_KEY.
pip install algenta-sdk # Python 3.12+
npm install algenta-sdk # TypeScript / JavaScript, Node.js 18+
Both clients read ALGENTA_API_KEY from the environment and default to Algenta's hosted API at https://api.algenta.ai.
Python — note the import name is decision_engine (see Legacy names):
from decision_engine import AlgentaClient
client = AlgentaClient() # reads ALGENTA_API_KEY; defaults to https://api.algenta.ai
datasets = client.list_datasets(search="orders", compact=True) summary = client.get_dataset_summary(datasets.datasets[0].dataset_id) result = client.query_with_metadata( { "dataset_id": summary.dataset_id, "metric": {"hint": "gross_revenue"}, "aggregation": "sum", } ) print(result.data.result)
TypeScript:
import { AlgentaClient } from "algenta-sdk";
const client = new AlgentaClient(); // reads ALGENTA_API_KEY; defaults to https://api.algenta.ai
const datasets = await client.listDatasets({ search: "orders", compact: true }); const summary = await client.getDatasetSummary(datasets.datasets[0].dataset_id); const result = await client.queryWithMetadata({ dataset_id: summary.dataset_id, metric: { hint: "gross_revenue" }, aggregation: "sum", }); console.log(result.data.result);
Self-hosted engine? Point the client at your own deployment — AlgentaClient(base_url="http://localhost:8000") in Python, new AlgentaClient({ baseUrl: "http://localhost:8000" }) in TypeScript — and use the API key provisioned by your operator. The self_hosted and air_gapped deployment profiles fail closed: they never silently fall back to Algenta's cloud. Framework integrations in thyn-ai/algenta-integrations take the opposite default on purpose: they are self-hosted-first, resolve their endpoint from ALGENTA_BASE_URL or an explicit base_url, and never default or fall back to the hosted API.
The full API surface — governed queries, connectors, simulations, jobs, triggers, agent runs, decisions, repository intelligence, and the TypeScript local Runtime facade — is documented in packages/python-sdk/README.md and packages/ts-sdk/README.md, with runnable projects in examples/. The MCP server lives in this repository (see MCP server above); framework integrations (LangChain, LlamaIndex, Vercel AI SDK, and more) live in the companion repository thyn-ai/algenta-integrations.
Both SDKs raise the same exception taxonomy. Every error carries the HTTP status, the engine's machine-readable error_code, and — in Python — the engine-assigned request_id; validation failures additionally expose per-field details via field_errors (Python) / fieldErrors (TypeScript).
| Exception | HTTP status | Raised when | Retried by default |
|---|---|---|---|
AuthenticationError | 401 | Missing or invalid API key | No |
NotFoundError | 404 | Resource does not exist | No |
ValidationError | 422 | Request failed schema validation | No |
RateLimitError | 429 | Quota or rate limit exceeded | Yes — honors the engine's Retry-After (retry_after / retryAfter, default 60s) |
ServerError | 5xx | Engine-side failure | Yes — exponential backoff |
DecisionEngineError | any | Base class for all of the above | — |
Transient network errors are retried on the same policy as 5xx responses. The Python SDK additionally never retries one rate-limit code, inline_preview_rate_limited.
| Setting | Python | TypeScript | Default |
|---|---|---|---|
| Request timeout | timeout (seconds) | timeout (milliseconds) | 120 |
| Retries per request | max_retries | maxRetries | 3 |
The SDK was renamed to Algenta partway through its history. For backward compatibility, the legacy names below still work — existing code and deployment configurations do not need to change:
algenta-sdk, but the importable module remains decision_engine: from decision_engine import AlgentaClient.CodnaClient (and AsyncCodnaClient in Python) remain exported as aliases of AlgentaClient in both SDKs.DE_API_KEY, DE_BASE_URL, and ALGENTA_API_URL are still accepted alongside the canonical ALGENTA_API_KEY and ALGENTA_BASE_URL.The published API contract guarantees a 90-day deprecation window (DEPRECATION_WINDOW_DAYS) before any legacy name is removed.
The engine's compute kernels — simulation, scoring, and local query execution — are written in Mojo and are proprietary. They are distributed as signed algenta-runtime-native wheels and are not part of this repository.
What is open, here and under Apache-2.0: both SDKs, the published API contract they are generated from, the client/runtime wire protocol they speak, and runnable examples — including examples/mojo-quickstart/, a minimal end-to-end walkthrough of calling the native runtime through the SDK.
This repository contains Algenta's Python and TypeScript client SDKs and the official MCP server (packages/mcp/), licensed under Apache-2.0 (see LICENSE and NOTICE).
The Algenta engine itself is closed source and is not contained in this repository. Engine licensing, device entitlements, worker limits, concurrency limits, and Server Compute Units are enforced independently by the engine, subject to the separate Algenta Engine license.
The SDK is a plain HTTP client. It holds no license-signing keys, no entitlement-enforcement logic, and no secret shared with the engine — every entitlement claim is independently verified and enforced by the closed engine, never by this SDK. Fork it, delete every check in it, or replace it with your own HTTP client entirely — modifying or replacing this SDK does not change the execution capacity licensed to an Algenta engine. See SECURITY.md for what that means for vulnerability reports.
Algenta does not require hosted inference or telemetry for execution. Paid licenses expand local execution and governance capacity rather than charging per SDK call.
Every release built by release.yml is tied to:
sdk-vX.Y.Z source tag in this repository;releases/).release.yml refuses to build or publish anything unless all of the above independently agree — see scripts/verify_release_authorization.py.
Each GitHub Release cut since signing was added (September 2026) carries, next to the wheel, the sdist and release-manifest.json:
.sigstore.json), signed by the release.yml run itself;multiple.intoto.jsonl), from the SLSA generic generator.To check an asset against both, with VERSION set to the release version (VERSION=1.0.15 for tag sdk-v1.0.15):
pipx run sigstore verify identity "algenta_sdk-${VERSION}-py3-none-any.whl" \
--bundle "algenta_sdk-${VERSION}-py3-none-any.whl.sigstore.json" \ --cert-oidc-issuer https://token.actions.githubusercontent.com \ --cert-identity "https://github.com/thyn-ai/algenta-sdk/.github/workflows/release.yml@refs/tags/sdk-v${VERSION}"
slsa-verifier verify-artifact "algenta_sdk-${VERSION}-py3-none-any.whl" \ --provenance-path multiple.intoto.jsonl \ --source-uri github.com/thyn-ai/algenta-sdk \ --source-tag "sdk-v${VERSION}"
A release published through release.yml's workflow_dispatch path was signed from the dispatched branch, so its certificate identity ends in @refs/heads/main instead of the tag; the bundle records which.
Both packages share one version number, since they wrap one API contract, and follow Semantic Versioning:
Release history lives in CHANGELOG.md.
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