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)
Query public astronomy catalogs through metadata-first TAP and ADQL tools.
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": {
"starfetch": {
"command": "npx",
"args": [
"-y",
"@starfetch-js/mcp"
]
}
}
}在终端中运行这条命令
claude mcp add starfetch -- npx -y @starfetch-js/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"starfetch": {
"command": "npx",
"args": [
"-y",
"@starfetch-js/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": {
"starfetch": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@starfetch-js/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6日
注册名称已通过 GitHub 账户 starfetch-js 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(0.3.0)于3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:Spec Driven Development, Remote Desktop Commander, Safe Fetch
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.
MCP server for fetching URLs, safe against SSRF, DNS rebinding, and redirect-to-internal attacks.
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。
Starfetch gives AI agents safe, reproducible access to public astronomy catalogs through the Model Context Protocol (MCP).
Ask an astronomy question in natural language. A Starfetch-enabled agent can select an appropriate service, inspect its live tables and columns, construct a bounded ADQL query, execute it, and return the result with the exact service, table, query, limit, units, and assumptions it used.
You: Find the 10 Gaia DR3 sources with the highest proper motion within 0.5
degrees of the Pleiades center at RA 56.75°, Dec +24.12°. What stands out?
Agent: selects Gaia → inspects metadata → runs bounded ADQL → returns catalog rows, exact ADQL, units, and assumptions
Representative captured result:
Service: ESA Gaia Archive
Table: gaiadr3.gaia_source Rows returned: 10 Query limit: TOP 10 / MAXREC 10
Highest returned proper motions:
Exact ADQL: SELECT TOP 10 source_id, ra, dec, pm, pmra, pmdec, parallax, parallax_error, phot_g_mean_mag, bp_rp, ruwe FROM gaiadr3.gaia_source WHERE CONTAINS(POINT('ICRS', ra, dec), CIRCLE('ICRS', 56.75, 24.12, 0.5)) = 1 AND pm IS NOT NULL ORDER BY pm DESC
Gaia, SIMBAD, VizieR, the NASA Exoplanet Archive, and IRSA are available as built-in service presets. Agents can also discover and query other public TAP services by URL. Starfetch remains TAP-native and keeps ADQL visible, so the agent workflow is convenient without becoming a scientific black box.
The local npm server is Starfetch's stable public connection path. It runs on your computer and can be registered with any compatible MCP client.
Register Starfetch with the agent client that will launch it. Running the MCP package by itself only starts a stdio server; it does not connect that server to an agent. Starfetch is also discoverable through the official MCP Registry.
Register Starfetch for the Codex CLI, IDE extension, and ChatGPT desktop app:
codex mcp add starfetch -- npx -y @starfetch-js/mcp
codex mcp list
These Codex surfaces share MCP configuration. See the official Codex MCP documentation.
Register Starfetch in user scope:
claude mcp add --scope user --transport stdio starfetch -- npx -y @starfetch-js/mcp
claude mcp get starfetch
See the official Claude Code MCP documentation.
Add this server entry to ~/.cursor/mcp.json for global use or .cursor/mcp.json for one project:
{
"mcpServers": { "starfetch": { "command": "npx", "args": ["-y", "@starfetch-js/mcp"] } } }
See the official Cursor MCP documentation.
Other MCP clients can use the same stdio command and arguments through their own server-registration interface:
command: npx
args: -y @starfetch-js/mcp
Restart or reload the client after registration, then ask a normal astronomy question. You should not need to write ADQL or name Starfetch tools in the prompt. Starfetch requires Node.js 22 or newer.
A remote MCP service runs on the internet and accepts MCP connections over HTTPS. No Starfetch package has to be installed or launched on the user's computer. Compatible clients can connect to the production endpoint:
https://starfetch-mcp-app-production-wumkqeiqaa-ew.a.run.app/mcp
The remote service is public, unauthenticated, bounded, and best effort. Do not send credentials, private archive URLs, sensitive personal data, or unbounded workloads. The local npm server remains the default when you want local control or when a client does not support remote Streamable HTTP MCP.
See the remote service's overview, privacy notice, support, and terms of use.
For a service-specific catalog question, Starfetch guidance teaches the agent to:
TOP, TAP MAXREC, or both;The agent should never present a timeout, availability failure, parse error, or query error as an empty scientific result. A successful zero-row result and a failed request are different outcomes.
Starfetch exposes tools for the complete workflow:
starfetch_list_presets
starfetch_registry_search starfetch_tap_availability starfetch_tap_capabilities starfetch_tap_tables starfetch_tap_columns starfetch_tap_query starfetch_tap_submit_job starfetch_tap_job_status starfetch_tap_job_wait starfetch_tap_job_fetch starfetch_tap_job_delete
Query tools return result data separately from diagnostics. They preserve the exact submitted ADQL and effective row limit for reproduction and review. Synchronous queries and async submissions send TAP MAXREC=100 when maxrec is omitted.
The remote HTTP service returns an opaque jobCapability with each async submission. Supply that value unchanged to every remote status, wait, fetch, or delete call. The capability remains usable while the remote job exists and the service signing secret is unchanged. Remote deletion is marked destructive so MCP clients can obtain user approval. The stdio MCP server and CLI keep their existing job-reference behavior and do not advertise remote-only fields.
Starfetch is a useful middle layer when an agent needs live public catalog data without turning the workflow into a black box:
Use an archive's own interface, PyVO/Astropy, or local analysis tools instead when you need authenticated/private archives, extensive local analysis, image data processing, or authoritative astrophysical interpretation.
The MCP server works without installing a filesystem skill. Starfetch carries the same canonical guidance through three overlapping layers:
| Layer | Role |
|---|---|
| MCP tool descriptions | Minimum metadata-first and bounded-query contract available to every MCP client |
| MCP prompts and resources | Discoverable workflows, ADQL guidance, service notes, and examples |
| Optional Starfetch skill | Rich multi-step behavior across longer agent interactions |
The server exposes the retrievable prompts query_astronomy_catalog, explore_service, run_cone_search, and troubleshoot_adql. Canonical Markdown resources are available under starfetch://guides/, starfetch://services/, and starfetch://examples/.
Prompt and resource support depends on the MCP client. Tool descriptions remain self-sufficient for basic safe operation when a client exposes tools only. The optional skill contains the full workflow, service references, and examples.
Install the skill when the agent client supports filesystem skills and you want the strongest multi-interaction behavior. The skill is recommended, not required by the MCP server.
Install the canonical skill directly from GitHub through skills.sh:
npx skills add https://github.com/starfetch-js/starfetch/tree/main/packages/skill/skill/starfetch
Inspect or install the packaged skill:
npx -y @starfetch-js/cli skill print
npx -y @starfetch-js/cli skill install --target codex npx -y @starfetch-js/cli skill install --target claude-code --scope project npx -y @starfetch-js/cli skill install --target cursor
Install into a custom final skill directory with:
npx -y @starfetch-js/cli skill install --path ./starfetch-skill
Use --dry-run to preview file actions. Default destinations are:
~/.codex/skills/starfetch~/.claude/skills/starfetch.codex/skills/starfetch.claude/skills/starfetch.cursor/rules/starfetch.mdcCodex and Claude Code default to user scope. Cursor defaults to project scope because its rules are project files.
Starfetch is designed for public astronomical Table Access Protocol services. It currently provides:
gaia, simbad, vizier, exoplanetarchive, and irsa;Starfetch does not accept credentials or implement authenticated TAP workflows. The M
只显示了开头部分;其余内容请在仓库中阅读