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Sancho Fetch

by panth-netversion 0.3.1i★ –iRuns on your computer
Registry nameio.github.panth-net/sancho-fetch

Install

Overview

Description from the maker (original English)

Local-first public-data MCP server that writes inspectable records and working files.

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: Docs, sheets & office work

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

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

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

Download the maker’s .mcpb file

The link goes to the maker’s own file; we do not host or repackage it. Open the file and Claude Desktop installs it.

Run this in your terminal

claude mcp add sancho-fetch -- uvx sancho-fetch mcp serve --workspace --transport stdio

This one needs values on its command line, so copy the settings and fill them in.

Or copy the settings yourself

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

{
  "mcpServers": {
    "sancho-fetch": {
      "command": "uvx",
      "args": [
        "sancho-fetch",
        "mcp",
        "serve",
        "--workspace",
        "--transport",
        "stdio"
      ]
    }
  }
}

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 needs values on its command line, so copy the settings and fill them in.

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "sancho-fetch": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "sancho-fetch",
        "mcp",
        "serve",
        "--workspace",
        "--transport",
        "stdio"
      ]
    }
  }
}

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 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account panth-net, 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 Docs, sheets & office worki

  • More stars than 0% of the other 3540 servers in this category
  • Published to the registry more recently than 38% of the other 3540 servers in this category
  • Basic checks equal to or better than 100% of the other 3540 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 Sancho Fetch 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 (0.3.1) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv), MCPB on your computer.

What can I use instead?

In the same category: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

Alternatives

Servers in the same category from other makers, sorted by stars.

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

Agent-Native Google Calendar - manage events, sync, and public booking

Runs in the cloud★ 7,620MITUpdated 2 months ago
Install

Excel MCP Server

by haris-musa

Lets AI create and edit Excel files itself, including formulas, charts and PivotTables, without Excel installed.

Runs on your computer★ 4,276MITUpdated 7 days ago
Install

Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.

Runs on your computer★ 847MITUpdated 4 days ago
Install

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.

Sancho Fetch

Ask your AI for public data. Get real files on your computer.

The fastest way in: tell your AI

Open your AI's code mode -- Claude desktop app -> Code tab, or ChatGPT desktop app -> Codex -- pick any folder, and paste this:

Install Sancho Fetch from PyPI (uv tool install sancho-fetch) and set it

up on this computer. If uv isn't installed, tell me, then install it

first. When you're done, tell me whether the install succeeded. Then

explain in plain English, no jargon: what the .env file is, how to use it,

where it is on my computer, and open it for me so I can paste API keys

straight into it. Give me a few examples of data sources that need a free

API key and a few examples of sources that don't need a key. Tell me where

my downloaded data gets saved, and how I update Sancho later. Then run a

short example data fetch using the World Bank so I can see where the data

was saved. Finally tell me a few natural language examples I can tell you

to fetch data so I can get a feel for how to use sancho-fetch and remind

me that 1) I can use it anywhere as long as I'm in a LLM Desktop app's

Code tab (e.g. ChatGPT Desktop or Claude Desktop), and 2) that I can ask

AI to add new data sources by itself since sancho-fetch is built in a way

that it's easily extensible (aka you can add more to it and the AI will do

the heavy lifting and connect the new data source).

That's the whole install.

You do not need to download or clone this repository. The two commands the AI runs are:

uv tool install sancho-fetch

sancho setup

Install once, use everywhere. Sancho installs once on your computer and connects to the AI apps it finds (Claude Desktop, ChatGPT/Codex, VS Code, Cursor). At the end of setup it tells you plainly which apps are ready and which just need a restart or a click.

To use Sancho, just ask for data and mention "sancho" in plain English, or type `/sancho` in Claude Code to feel cool.

What it does

  • In your AI's Code mode you ask: *"get county-level asthma rates for Ohio."* You can be working in any folder -- Sancho always knows where its home folder is.
  • Your AI uses Sancho to pull from 120+ public sources (Census, World Bank, FDA, USGS, FEMA, ...) and hands you a file that opens in Excel.
  • Everything is saved on your computer.

Before you begin

The normal prerequisite is uv. uv installs Sancho in isolation and can obtain a compatible Python without replacing your computer's system Python. First setup needs an internet connection. API keys are not required for installation or the World Bank example; provider-specific keys can be added later.

Get started (about 2 minutes)

Install straight from PyPI.

1. Open your AI's code mode.

  • Claude: Claude desktop app -> Code tab -> new session -> pick any folder where you want your data to live.
  • ChatGPT: ChatGPT desktop app -> Codex -> open that folder.

2. Paste the install request from the top of this page.

The AI installs everything, shows you your first data file, and walks you through where everything lives.

3. Restart the apps Sancho asks you to restart. Setup ends with a short report; if an app needs a restart or one extra click, it says so in plain words.

NOTE: Before using, make sure to add API keys for any sources you want to use.

Many sources need no key (World Bank, USGS, FEMA, openFDA, ...). Your AI will tell you when an API key is needed. You can either:

  1. Open the .env file in the sancho-workspace folder and paste your key there; or
  2. Ask your AI to open the keys file for you (sancho env open). Paste the key into the opened file, **don't paste your key

into the chat**.

Setup normally creates .env from .env.example. If .env is missing, sancho env open creates and opens it. To do this manually, copy .env.example in the same folder, keep the original template, and name the copy .env.

Both files may be hidden:

  • macOS Finder: press Cmd+Shift+. (Command + Shift + period).
  • Windows File Explorer: select View -> Show -> Hidden items.

@Developers, fyi Sancho is designed to read key names only, not values.

Prefer the GitHub repository, or installing without an AI app?

For contributing, custom module development, or offline installs, work from the repository folder instead. Install GitHub Desktop (free), then on this repository's page click Code -> Open with GitHub Desktop -> Clone.

Note: Avoid placing the Github folder in a folder that is within iCloud/OneDrive (e.g. Documents folder in iCloud). This causes issues with file syncing and speed.

Then double-click installers/Install Sancho.command (macOS) or installers/Install Sancho.bat (Windows); on Linux run bash installers/setup.sh.

  • macOS blocks the first open (the installer is not notarized): System Settings -> Privacy & Security -> scroll to the blocked-file message -> Open Anyway -> open it again.
  • Windows: at "Windows protected your PC", click More info -> Run anyway.

Everyday use

  • In Claude Code / Codex, just ask for data. In Claude Code you can also type `/sancho` and `/sancho-update` directly.

After installation, use a Code session. Sancho is installed

computer-wide, so you do not need to add the sancho-fetch folder in future

sessions. In Claude Desktop, select the Code tab. In **Codex, start a

Code chat**. Regular chats cannot access your local Sancho installation.

  • There are system instructions to make Sancho return non-technical details of each data pull, so if you want these technical details returned, tell your AI:

*"turn on Sancho developer mode."*

  • Something off? Ask your AI to run sancho ready -- it checks your setup and reports what's wrong, without changing your setup. To actually fix problems, ask your AI to run sancho doctor --fix.

Where your files land

your folder/

sancho-downloads/ # <-- files you have downloaded via chatting with AI sancho-workspace/ source/ # managed data modules custom/ # your own modules -- never overwritten when updating Sancho playbooks/ # your repeatable workflows fetched-data/ # faithful archive of every fetch (don't edit - this is a cache so we don't have to use API calls unnecessarily) analysis-data/ # your derived work outputs/ # reports, dashboards, exports logs/ # what Sancho did, when, and why update-backups/ # snapshots before every update .env # your API keys (never logged, never printed)

Every fetch writes a working file you open -- into sancho-downloads/ in the folder that you're working in -- and a faithful archive/cache copy in sancho-workspace/fetched-data/ so repeat requests reuse cached data.

Tables arrive as Excel .xlsx with codes like 01003 kept intact; maps stay GeoJSON/KML; nothing is converted in a way that loses information. Filenames start with the date: 2026-06-08_194211_alabama-population.xlsx.

Add your own data sources

Tell your AI:

Create a Sancho module for [that API / that agency's data / this file I

receive every month].

It's built under custom/, works like the built-in sources, and Sancho updates never overwrite the folder.

A good example of this is, Sancho fetches from Washington DC's and New York City's open data portals, which use a common API/open data portal format. The AI can be asked to create a module for other cities and will intelligently check on its own whether the new city uses the same format or not, and if it does, will reuse the same module code format (and otherwise, create a new one). You'd be surprised at how many cities use the same format so give it a try if you're working in a geographic regional level that is not already covered by Sancho's built-in modules.

Updates

Just ask your AI:

Update Sancho.

The AI upgrades the sancho command from PyPI (uv tool upgrade sancho-fetch) and then migrates your workspace safely, with a backup and a rollback command.

Working from the GitHub repository instead? In GitHub Desktop: Fetch origin -> Pull origin, then tell your AI *"update Sancho."*

When updating, your own files (custom/, playbooks/, fetched-data/, .env, ...) are never touched.

If you want Sancho to stop mentioning new versions in chats (which it will do once every 2 weeks), simply set SANCHO_UPDATE_NUDGE=false in .env to turn it off.

Uninstalling

Same as installing: paste one request to your AI in a Code session:

Uninstall Sancho Fetch from this computer: run sancho uninstall, then

uv tool uninstall sancho-fetch. Keep my sancho-workspace and

sancho-downloads folders -- that is my data and my API keys. Tell me when

it's done and what was removed.

(Those two commands are the whole uninstall if you'd rather run them yourself.)

Sancho only removes what it installed: its skills and its entries in your AI apps. Anything you edited or created yourself is left alone and reported.

Your sancho-workspace/ folder (fetched data, custom modules, .env keys) and your sancho-downloads/ files are always kept. Deleting data is a separate, deliberate step that asks for confirmation first -- ask your AI, or run sancho uninstall --help to see how.

Privacy Policy

Sancho runs on your computer and keeps your data there. Fetches go directly from your machine to the public data provider you chose; API keys are read from your local .env and sent only to that provider. Sancho has no telemetry. Full details: docs/PRIVACY.md.

More documentation

  • CHANGELOG.md -- what changed in each release.
  • README_ALL_INSTRUCTIONS.md -- full operator/AI reference.
  • project-docs/MCP_SERVER_SETUP_CLAUDE_CHATGPT_WEB.md -- MCP setup details for desktop and web clients.
  • project-docs/MODULE_CREATION_GUIDE.md -- how your AI builds new data modules.

Hosting your own version of Sancho

While Sancho is designed to run on your own computer, you can also host it on a server so that users can access it via web rather than needing Claude/Codex desktop apps.

The idea with hosting was primarily to support organizations hosting hands-on workshops for users who may not have the technical skills to install Sancho on their own computers.

  • hosting/README.md -- hosted demo endpoint for events.

For AI assistants

If you are an AI assistant, do not operate from this quick start. Read README_ALL_INSTRUCTIONS.md, then follow CLAUDE.md or AGENTS.md.

License

Code is licensed under MPL 2.0; documentation under CC BY 4.0 unless noted. The Sancho name, logo, and brand assets are protected separately -- see LICENSE, NOTICE, LICENSE-DOCS.md, and INTENDED_USE.md.

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