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Starfetch

by starfetch-jsversion 0.3.0i★ –iRuns on your computer
Registry nameio.github.starfetch-js/starfetch

Install

Overview

Description from the maker (original English)

Query public astronomy catalogs through metadata-first TAP and ADQL tools.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "starfetch": {
      "command": "npx",
      "args": [
        "-y",
        "@starfetch-js/mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add starfetch -- npx -y @starfetch-js/mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "starfetch": {
      "command": "npx",
      "args": [
        "-y",
        "@starfetch-js/mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "starfetch": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@starfetch-js/mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account starfetch-js, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32568 servers in this category
  • Published to the registry more recently than 19% of the other 32568 servers in this category
  • Basic checks equal to or better than 100% of the other 32568 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Starfetch safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.3.0) reached the registry 3 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, FlyDocs

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday
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FlyDocs

by flydocs.ai

Spec-driven development workflow: your agent works issues, sessions and the status lifecycle.

Runs on your computerUpdated today
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Starfetch

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:

  • Gaia DR3 66780900298410496: 244.48 mas/yr
  • Gaia DR3 66524409149512064: 184.50 mas/yr

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.

Start here

  • Connect an agent
  • What the agent does
  • Why Starfetch?
  • Reliability without hidden assumptions
  • Optional Starfetch skill
  • Supported scope
  • CLI and TypeScript
  • Run the Gaia proper-motion demo
  • Development

Connect an agent

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.

Local npm server

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.

Codex

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.

Claude Code

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.

Cursor

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.

Remote MCP

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.

What the agent does

For a service-specific catalog question, Starfetch guidance teaches the agent to:

  1. choose an explicit service preset or public TAP URL;
  2. check service availability when appropriate;
  3. inspect relevant tables and the selected table's columns;
  4. construct ADQL only from discovered schema information;
  5. bound exploratory work with ADQL TOP, TAP MAXREC, or both;
  6. execute the smallest useful query;
  7. return the service, table, exact ADQL, effective limit, format, units, and relevant assumptions;
  8. return to metadata after a schema or syntax failure instead of guessing.

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.

Why Starfetch?

Starfetch is a useful middle layer when an agent needs live public catalog data without turning the workflow into a black box:

  • it inspects live schemas instead of guessing table and column names;
  • it bounds public-service queries by default and preserves service failures;
  • it returns exact ADQL, limits, units, and assumptions for reproduction;
  • it provides one metadata-first interface across several TAP services; and
  • its CLI and TypeScript library can reproduce an agent's query outside the agent client.

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.

Reliability without hidden assumptions

The MCP server works without installing a filesystem skill. Starfetch carries the same canonical guidance through three overlapping layers:

LayerRole
MCP tool descriptionsMinimum metadata-first and bounded-query contract available to every MCP client
MCP prompts and resourcesDiscoverable workflows, ADQL guidance, service notes, and examples
Optional Starfetch skillRich 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.

Optional Starfetch skill

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 user scope: ~/.codex/skills/starfetch
  • Claude Code user scope: ~/.claude/skills/starfetch
  • Codex project scope: .codex/skills/starfetch
  • Claude Code project scope: .claude/skills/starfetch
  • Cursor project scope: .cursor/rules/starfetch.mdc

Codex and Claude Code default to user scope. Cursor defaults to project scope because its rules are project files.

Supported scope

Starfetch is designed for public astronomical Table Access Protocol services. It currently provides:

  • built-in presets for gaia, simbad, vizier, exoplanetarchive, and irsa;
  • VO registry search for additional TAP endpoints;
  • VOSI availability, capabilities, table, and column metadata;
  • bounded synchronous ADQL queries;
  • explicit TAP/UWS async job submission, status, wait, fetch, and deletion;
  • VOTable, CSV, and TSV requests, plus safe JSON and JSONL conversion;
  • exact query and limit diagnostics.

Starfetch does not accept credentials or implement authenticated TAP workflows. The M

Only the beginning is shown; read the rest in the repo

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