Cldf MCP

Name: Cldf MCP
Author: hsouf

by hsoufversion 0.1.0i★ –iRuns on your computer

Registry nameio.github.hsouf/cldf-mcp

Install

Overview

Description from the maker (original English)

WALS typology joined with Glottolog classification, with provenance and family-aware counts.

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User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

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

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

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": {
    "cldf": {
      "command": "uvx",
      "args": [
        "cldf-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add cldf -- uvx cldf-mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "cldf": {
      "command": "uvx",
      "args": [
        "cldf-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": {
    "cldf": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "cldf-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 hsouf, 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 32686 servers in this category
Published to the registry more recently than 74% of the other 32686 servers in this category
Basic checks equal to or better than 100% of the other 32686 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 Cldf MCP 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 (0.1.0) reached the registry 13 days 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) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Microsoft Exchange Online MCP

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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.

cldf-mcp

An MCP server that gives AI assistants grounded access to cross-linguistic data published in the CLDF format. Version 0.1 ships with:

[WALS](https://wals.info), the World Atlas of Language Structures: 192 typological features (word order, phonology, morphology…) for 2,660 languages, with sources for every datapoint;
[Glottolog](https://glottolog.org): the catalog of the world's ~27,000 languoids, their classification, alternate names, endangerment and description status.

Language models know WALS exists but are unreliable on specifics: which value a language has for feature 85A, or how many languages combine SOV order with prepositions. This server returns the actual data, with the release it came from and the reference behind it.

What makes it different from a lookup table

Family-aware counts. Related languages inherit features, so "400 languages do X" can mean "three big families do X". Every count comes with the number of distinct families (from Glottolog) and WALS genera, plus the share of the largest family, so the model can tell a cross-linguistic tendency from the signature of one lineage. WALS's balanced 100- and 200-language samples are available as filters.
Provenance everywhere. Each answer names the dataset, release and citation; datapoints carry their bibliographic sources and page numbers.
No silent guessing. bsq is WALS's code for Basque and the ISO code for Bassa, so the server asks instead of picking one. "No data" is never reported as "absent".
Pinned, verified data. Datasets are fetched from tagged releases and checked against SHA-256 checksums before loading.

Quick start

Requires Python 3.11+ and uv (or pip).

Claude Code

claude mcp add cldf -- uvx cldf-mcp

Claude Desktop and other clients that use an mcpServers config:

"mcpServers": { "cldf": { "command": "uvx", "args": ["cldf-mcp"] } } }

On first use the server downloads the pinned releases (about 40 MB) and builds a local SQLite database (about 35 MB) in a few seconds. To do this ahead of time:

uvx cldf-mcp setup

Then ask things like:

*Which languages in WALS are SOV but use prepositions? Are they spread across families?*
*Is "VSO implies prepositions" a real tendency? Check it within the WALS 200-language sample.*
*Give me Basque's word-order features, with sources.*
*How does WALS cover the Austronesian family? Which branches have the most data?*

Tools

Tool	What it does
`list_datasets`	Loaded datasets, release versions, coverage, licenses and citations
`find_language`	Names (including alternate names and misspellings), ISO 639-3 codes, Glottocodes or dataset codes → ranked candidates with family, macroarea and which entries have data
`search_features`	Keyword search over feature names, chapters and value labels → feature IDs and possible values
`get_feature`	Definition, chapter, authors and value distribution, counted by languages, families and genera; optional filters by macroarea, family/subgroup or WALS sample
`get_values`	Language × feature grid with values, comments, sources and full citations; unresolvable names are reported with candidates instead of failing the call
`language_profile`	Everything about one language: Glottolog identity, lineage, endangerment, description status and all feature values
`filter_languages`	Languages matching up to 8 conditions (AND, with `exclude`), across datasets, with the denominator (languages coded for all conditions) and family counts
`crosstab`	Two features cross-tabulated: languages, families, genera and largest-family share per cell, zero cells kept, optional macroarea breakdown
`classification`	Glottolog lineage, children (with how many dataset entries fall under each), sisters
`get_source`	Full bibliographic references for the source IDs cited in datapoints

Resources:

cldf://guide/typology-caveats: how to use counts responsibly (sampling bias, areal effects, coverage, citation). The server's instructions point the model to it.
cldf://datasets: versions, licenses and citations of the loaded data.

All tools are read-only and work offline once the data is prepared.

Configuration

Setting	Default
`--data-dir` / `CLDF_MCP_DATA_DIR`	`~/.cache/cldf-mcp` (Linux), `~/Library/Caches/cldf-mcp` (macOS), `%LOCALAPPDATA%\cldf-mcp` (Windows)
`--config` / `CLDF_MCP_CONFIG`	none: extra TOML to add or override datasets (experimental, see below)
`--transport`	`stdio`; `streamable-http` with `--host` / `--port` for remote use

Other commands: cldf-mcp info (where data lives, whether it is current) and cldf-mcp setup --force (rebuild).

Adding a dataset (experimental)

Any CLDF StructureDataset whose languages carry Glottocodes can be loaded alongside WALS. Feature tools, family counting and cross-dataset filters work on it automatically:

# my-datasets.toml

[datasets.mydata] title = "My typological survey" role = "features" version = "v1.0" base_url = "https://raw.githubusercontent.com/me/mydata/v1.0/cldf/" # or: local_path = "/path/to/cldf" metadata = "StructureDataset-metadata.json" license = "CC-BY-4.0" citation = "Me. 2026. My typological survey."

[datasets.mydata.files] # every file the loader needs, with optional sha256 checksums "StructureDataset-metadata.json" = "" "languages.csv" = "" "parameters.csv" = "" "codes.csv" = "" "values.csv" = ""

cldf-mcp setup --config my-datasets.toml

Data, licenses and citation

The server code is MIT-licensed. The data is not part of this package: it is downloaded from the original releases, which are licensed under CC-BY-4.0. If you publish results obtained with this server, cite the datasets (see DATA_LICENSES.md):

Dryer, Matthew S. & Haspelmath, Martin (eds.) 2013. *The World Atlas of Language Structures

Online.* Leipzig: Max Planck Institute for Evolutionary Anthropology. https://wals.info

(CLDF release v2020.6)

Hammarström, Harald & Forkel, Robert & Haspelmath, Martin & Bank, Sebastian. 2026. *Glottolog 5.3.*

Leipzig: Max Planck Institute for Evolutionary Anthropology. https://glottolog.org

This is an independent project and is not affiliated with the WALS, Glottolog or CLDF teams.

Limitations

WALS reflects the literature up to about 2013, and most features are coded for a few hundred languages. Percentages are of coded languages, not of the world's languages.
Family counts follow Glottolog, which does not recognise proposed macro-families (e.g. Altaic). Of the 17 WALS languages without a Glottocode, 10 are matched to a Glottolog family through WALS's family or genus name; the other 7 keep WALS's own label (e.g. "Niger-Congo").
Glottolog's full bibliography is not bundled; its references are returned as links.

Roadmap

0.2: Grambank, the first dataset that overlaps with WALS, with side-by-side comparison of related features.
0.3: PHOIBLE sound inventories and Lexibank wordlists (get_inventory, get_forms).

Development

git clone https://github.com/hsouf/cldf-mcp && cd cldf-mcp

python -m venv .venv && . .venv/bin/activate pip install -e ".[dev]" pytest # offline tests on small fixtures (tests/fixtures) pytest -m network # downloads the real pinned releases and checks known WALS counts ruff check src tests && ruff format --check src tests

See RELEASING.md for publishing to PyPI and the MCP Registry.

Cldf MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Microsoft Exchange Online MCP

README from the maker

cldf-mcp

What makes it different from a lookup table

Quick start

Tools

Configuration

Adding a dataset (experimental)

Data, licenses and citation

Limitations

Roadmap

Development