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)
Intent-bound action authorization for AI agents: policy, human approval, and a signed audit trail.
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。
DELEGO_HOME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 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"delego": {
"command": "uvx",
"args": [
"delego"
],
"env": {
"DELEGO_HOME": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add delego --env DELEGO_HOME=your-value -- uvx delego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": {
"delego": {
"command": "uvx",
"args": [
"delego"
],
"env": {
"DELEGO_HOME": "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": {
"delego": {
"type": "stdio",
"command": "uvx",
"args": [
"delego"
],
"env": {
"DELEGO_HOME": "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。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
DELEGO_HOME env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。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
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6日
注册名称已通过 GitHub 账户 Delego-Dev 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
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
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。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.3.4)于5个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:Spec Driven Development, Remote Desktop Commander, topo^alpin
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.
Avalanche bulletins and mountain weather forecasts for any place in the Alps.
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。
Website: delegohq.com · Docs: delegohq.com/docs · Spec: Delego-Dev/specification
Intent-bound action authorization for AI agents. It sits between an agent and whatever credential broker holds the user's secrets, and it answers the one question brokers don't: *is this specific action the thing the human actually asked for?*
agent ──propose──▶ delego ──if allowed──▶ credential broker ──▶ service
(LLM) (policy + (Agent Vault / (bank, approval + OneCLI / SaaS, audit) Browser Use…) API) │ └── needs_approval ──▶ human (CLI)
📜 Protocol: delego implements protocol 0.3 of the open delego wire specification — canonicalization, the policy schema, intent/fingerprint binding including the §4.2 query-fold, and the signed audit chain. The authorization token (spec §9) is an optional profile, not yet implemented.
The "agent gets its own scoped credential, and never holds the user's secret directly" pattern is now a crowded, converging space — Infisical's Agent Vault, OneCLI, Browser Use, Nango, and others all do credential brokering.
The harder problem sits one level up — the confused deputy: the agent holds a *valid* credential, a prompt injection redirects it, the scope *covers* the action, so the broker happily injects the secret and the action goes through. The credential is the wrong place to catch this — it's valid. OAuth tokens carry no commitment to the original instruction.
Authorising the *action* (not just the credential) is an active area — see deterministic policy engines (OPA/Cedar, Permit), human-in-the-loop approval (HumanLayer), MCP gateways/firewalls, and the "pre-action authorization" line of research. delego is a small, deterministic, local, Apache-2.0 reference for it: no LLM in the decision path, no credential custody, approvals bound to the exact action fingerprint, and a signed, hash-chained audit trail — riding the existing broker layer rather than competing with it.
BrokerAdapter interface — you ride the existing layer instead of rebuilding it.verify(expected_head=…); for key safety, use an HSM/KMS. See SECURITY.md.pip install delego # the `delego` library + CLI
delego-mcp server (MCP is an optional extra)delego init # creates ~/.delego with signing keys and an example policy delego policy # inspect the active policy
To run the full loop end-to-end from a clone — an allowed read, a forbidden deny, an over-cap deny, an approval flow, the confused-deputy guard refusing a substituted action, and audit-chain tamper detection (no agent or live service needed):
git clone https://github.com/Delego-Dev/delego && cd delego
pip install -e ".[dev]" python examples/demo.py pytest
delego policy # show the active policy
delego pending # list actions awaiting approval delego approve apr_xxxx # release a parked action (or: delego deny apr_xxxx) delego log -n 20 # read recent receipts delego verify # check the audit chain (hashes, linkage, signatures)
delego ships an MCP server (delego_mcp) over stdio — install it with the mcp extra: pip install "delego[mcp]". Register it in your MCP config (for Claude Code, .mcp.json at the project root) so the agent can propose actions. Set DELEGO_HOME to keep the policy, signing keys, and ledger project-scoped under .claude/.delego:
{
"mcpServers": { "delego": { "command": "delego-mcp", "env": { "DELEGO_HOME": "/abs/path/to/project/.claude/.delego" } } } }
Initialise that home and approve from the same one (the CLI and MCP server must share a home):
delego --home .claude/.delego init # keys, example policy, and a .gitignore
delego --home .claude/.delego pending # ...then: delego --home .claude/.delego approve apr_xxxx
If DELEGO_HOME is unset, the CLI also auto-uses ./.claude/.delego when run from the project root, falling back to ~/.delego. (Use an absolute path in the MCP env, since the server's launch directory isn't guaranteed.)
Tools exposed:
| tool | what it does |
|---|---|
delego_propose_action | submit an action; returns allow / deny / needs_approval |
delego_resolve_action | complete an approved action (fingerprint must match) |
delego_pending | list actions awaiting human approval (read-only) |
delego_audit_tail | read recent receipts |
delego_show_policy | show the active policy |
Approving and denying are deliberately not exposed over MCP — the agent that proposed an action must never be able to approve it; a human decides out-of-band.
Typical flow: the agent calls delego_propose_action. If it comes back needs_approval with an approval_id, a human runs delego approve , then the agent calls delego_resolve_action with the identical action to complete it.
A rule matches on method / host / path (glob) / path_contains, decides allow or needs_approval, and can attach constraints. Order is forbidden (hard deny) → rules (first match wins) → default. A matched rule whose constraints fail becomes a deny (fail-closed). See policy.example.yaml.
rules:
Supported constraints: amount (cap + currency), allow_list (field-in-set), rate_limit (max per minute/hour/day, counted from the ledger).
Three ways to use it, lowest friction first:
delego init, add the delego-mcp server to your MCP config, and your agent proposes actions instead of executing them. No code.pip install delego, write a policy + a BrokerAdapter, and call fw.propose(...) in your tool-call path.Firewall in an HTTP API so many agents share one decision point and one audit chain.The one extension point is the broker — where your credential lives and the authorised action actually runs. delego never holds the secret:
NullBroker (default) — simulates execution; for demos and tests.HTTPProxyBroker(gateway_url) — forwards the authorised action to an external credential gateway (OneCLI / vault / proxy) that injects the secret upstream.execute(action) -> dict against the BrokerAdapter protocol in delego/brokers.py.▶ [Delego-Dev/sample-app](https://github.com/Delego-Dev/sample-app) — a FastAPI service built on the published package, with the full propose → approve → resolve loop and a copy-paste curl walkthrough. The best starting point for building your own.
See [ROADMAP.md](ROADMAP.md) for where delego is going and where to help.
/orders?to=me and /orders?to=attacker are different actions), the confused-deputy guard, intent-bound + single-use human approvals, the signed, hash-chained audit ledger with verification and an external head-anchor check (delego verify --expected-head), and the §9 authorization token (optional profile) — a short-lived, EdDSA-signed JWS a separated broker verifies before injecting a credential (build_firewall(..., mint_tokens=True); verify_token / require_fingerprint).delego daemon): one long-running process owns the ledger, so every client routes through it and rate_limit is exact across all of them — not just one host's file lock. The CLI's approve/deny/pending auto-route to a running daemon. Optional: with no daemon, everything works file-backed as before.NullBroker holds no credentials and makes no real request — it records what *would* be sent (for demos and tests). HTTPProxyBroker forwards an authorised action — and its authorization token — to an external credential gateway; or write your own against the BrokerAdapter protocol in delego/brokers.py.rate_limit is exact only among processes sharing one home on one host. Run `delego daemon` for exact rate limits across all clients (one writer). The daemon serializes one action in flight at a time (a reserve-then-execute throughput optimization, and a TCP transport for other hosts, are future work). Path globbing is coarse (** and * collapse).Licensed under the Apache License 2.0.