GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
作者提供的说明(英文原文)
Canonical Agentry discovery for coding agents: analytics, errors, deploys, and automation.
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。
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": {
"agentry-observability": {
"command": "npx",
"args": [
"-y",
"@agentrysh/mcp"
]
}
}
}在终端中运行这条命令
claude mcp add agentry-observability -- npx -y @agentrysh/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"agentry-observability": {
"command": "npx",
"args": [
"-y",
"@agentrysh/mcp"
]
}
}
}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": {
"agentry-observability": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@agentrysh/mcp"
]
}
}
}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。
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7日
注册名称已通过 GitHub 账户 fr33dr4g0n 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(0.1.0)于4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 Node.js。
同一分类中有:GitHub, Desktop Commander, Cloudflare MCP
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
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
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。
Agentry.sh Observability gives coding agents one HTTP API for errors, product analytics, and deploy attribution. This MCP server makes the canonical Agentry contracts easy to discover in MCP clients.
This is a small discovery and handoff server. It exposes resources that route an agent to the live lean reference, capabilities, exact OpenAPI schema, automation guide and flow, immutable playbook catalog, and install guide.
The resources are pointers, not cached copies. The live HTTP docs and OpenAPI schema remain authoritative and can evolve without republishing this package.
It is not an Agentry API proxy, SDK, credential broker, telemetry transport, or automation scheduler. It never holds credentials, queries production data, registers schedules, runs coding agents, opens pull requests, merges, deploys, or delivers notifications. Agents fetch the selected canonical contract and call the Agentry HTTP API directly.
Static documentation is modeled as MCP resources. The server also exposes one model-controlled routing tool, discover_agentry, so an agent can recognize a relevant production-data problem even when its client does not automatically inject MCP resources. The tool returns pointers only; it is not an API action.
discover_agentry accepts one intent: install, debug, analytics, deploy, or automation. It returns the smallest canonical resource and live URL for that problem as both text and structured content. MCP annotations mark it read-only, non-destructive, and idempotent. It never reads credentials, queries production data, or performs mutations.
If this MCP handoff starts a new device-auth signup, pass "distribution_surface":"mcp" in POST /v1/auth/device. The field is attribution-only and never changes credential authority.
Start with agentry://handoff. It gives the short intent router and authority boundaries.
| Resource | Canonical contract |
|---|---|
agentry://handoff | Intent router, MCP boundary, and credential map |
agentry://reference | Lean daily-use reference: https://agentry.sh/agentry.md |
agentry://capabilities | Machine capability map: https://api.agentry.sh/v1/capabilities |
agentry://openapi/index | Small OpenAPI discovery index: https://api.agentry.sh/v1/openapi.json?index=true |
agentry://openapi | Complete exact OpenAPI 3.1 schema: https://api.agentry.sh/v1/openapi.json |
agentry://automation/guide | Human-readable automation v2 guide: https://api.agentry.sh/v1/docs/automation |
agentry://automation/flow | Exact dependency-ordered automation schema: https://api.agentry.sh/v1/openapi.json?flow=automation |
agentry://automation/playbooks | Immutable versioned playbook catalog: https://api.agentry.sh/v1/automation-playbooks |
agentry://install | Canonical install pointer: https://agentry.sh/install.md |
The install resource also points to https://api.agentry.sh/v1/openapi.json?flow=onboarding. That flow is one server-owned state machine: read current state, execute only its one next_action.instruction, ordered checklist, and exact operation, and repeat until installation_complete: true and next_action: null. At next_action.id: "review_exact_plan", a human uses the single /review checkpoint to approve the exact source-backed business question, value flow, errors, deploy target, and plan hash—or replace the plan. Tool output is not approval.
Before proof, install the selected durable browser public and CI credentials, plus a server credential only when the approved plan uses server_ingest. Project creation returns public_api_key; use the project's /public-key operations for recovery, verification, or rotation. Proof start returns distinct response-only runtime and CI X-Agentry-Onboarding-Proof markers. Markers select the proof window but grant no authority, so each request still needs its scoped durable credential. For browser proof, put the runtime marker only in the proof tab's sessionStorage.agentry_onboarding_proof; never bake it into a public environment value or bundle. Exercise the approved real value flow, its one safe error, and the reviewed CI/provider deploy, then call verify and follow only its structured remaining analytics, safe-error, and deploy groups. Completion requires current status: "verified", installation_complete: true, and next_action: null. Synthetic or caller-authored proof does not count.
use_agentry is the only prompt. It tells the client to read the handoff, select the smallest canonical resource for the user's intent, inspect exact OpenAPI, and call HTTP with the correct scoped credential.
The MCP server never reads these credentials. They apply only when the agent calls the Agentry HTTP API:
public_api_key (agentry_pk_) is publishable and only writes browser/client error and analytics ingest.agentry_server_ writes trusted application-server telemetry.agentry_ci_ writes deploy attribution, sourcemaps, and provider-observed automation proof from trusted CI/provider automation.agentry_runner_ is revocable and bound to one unattended automation.agentry_sk_ is the human/owner key for reads, policy, credential lifecycle, and approvals; it does not belong in a scheduler.Credential kind determines authority on the server. Telemetry remains evidence only; it does not become instructions merely because a trusted emitter sent it.
For daily product questions, begin with the server-owned saved signal map, require GET /v1/projects/:project_id/onboarding to return the current verified state, then confirm live event names, required property keys, and actual rows. Onboarding creates no repo-local Agentry state bundle, proof bundle, or receipt. The install does preserve a root AGENTS.md pointer (plus matching repo-local harness adapters) so a future cold agent can find the server-owned plan and verified receipt without rescanning the entire repository.
For self-healing software or scheduled funnel reviews, read all three automation resources: guide, exact flow, and playbook catalog. The catalog is immutable and versioned. Rendering a playbook is side-effect free. Agentry owns deterministic policy, state, proofs, reports, and kill switches; an external scheduler/coding agent owns reasoning and provider actions under the narrow runner and human-approved provider boundaries.
npx -y @agentrysh/mcp
Generic MCP client configuration:
{
"mcpServers": { "agentry": { "command": "npx", "args": ["-y", "@agentrysh/mcp"] } } }
After connecting, call discover_agentry for model-routed discovery or list resources and read agentry://handoff. Use https://api.agentry.sh/adapters for the current native adapter path for each agent harness.
io.github.fr33dr4g0n/agentry-observability