Võro MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Võro MCP Serverlook up 'tulõma' in the Võro dictionary"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Võro MCP Server
An MCP server for working with the Võro language: local dictionary and corpus lookup, GiellaLT-backed analysis/spellcheck/grammar tools, and Neurotõlge translation.
What it's for
This MCP server gives language models practical tools for working with the Võro language. Võro is a lower-resource language, so general-purpose language models may make more mistakes with it than with widely supported languages such as English, or even Estonian.
By connecting the model to dictionaries, corpus search, morphological analysis, spellchecking, grammar checking, translation, and form generation, this server helps improve the model’s ability to understand, generate, correct, and translate Võro text.
It can be useful for tasks such as Võro translation, checking and improving generated text, exploring real usage examples, generating word forms, detecting unknown words, and supporting people who are learning or working with the Võro language.
Install
On Debian/Ubuntu, one command does the whole setup.
make setup # scripts/run_local_ubuntu.sh; see `make help` for every taskYou need make, Python, and the usual shell tools installed first. The setup
target installs the HFST/Divvun system binaries (adding the Apertium package
repo first if your system can't already find divvun-gramcheck), downloads the
SQLite datasets and the prebuilt Giella models, creates .venv, and installs
the package. Smoke-test it with make test.
Manual setup
For other platforms, or to see the pieces:
System binaries the Giella tools shell out to:
hfst-optimized-lookup,hfst-ospell,cg3,divvun-checker. On Debian/Ubuntu they come from the Apertium nightly apt repo:curl -fsSL https://apertium.projectjj.com/apt/install-nightly.sh | sudo bash sudo apt-get install -y hfst hfst-ospell cg3 divvun-gramcheck perl gawk bashThe package, into a virtualenv (
make install):python3 -m venv .venv . .venv/bin/activate pip install -e .Data and models, they are pulled from GitHub releases:
scripts/fetch_data.sh scripts/fetch_giella.shVerify the external tools resolved (prints JSON and exits):
vro-mcp-check
Tools
Tool | What it does |
| Dictionary lookup (en↔vro). |
| Full-text corpus search for real usage. |
| Fast check whether a word form has been seen. |
| List word forms in a text absent from the word bag. |
| GiellaLT morphological analysis. |
| GiellaLT generation for one exact lemma + tag analysis. |
| Token-level spellcheck with suggestions. |
| Sentence-level grammar check. |
| Flag Estonian-looking endings in Võro text. |
| Analyzer-verified fixes for a bad/unknown form. |
| Neurotõlge/TartuNLP translation. |
| Report database and external Giella tool availability. |
Most lookup tools accept a single word or a list for batched queries.
The open dictionary currently covers English↔Võro only.
Resources
Two Markdown grammar references are exposed over MCP:
vro://grammar/noun-cases: noun/adjective/numeral/pronoun declension.vro://grammar/verb-conjugation: verb conjugation, moods, tenses, voice.
Configuration
The data lives under data/ and is fetched for you. make setup (or make
data + make giella) downloads everything, so you normally configure nothing.
The fetch scripts honour VRO_DATA_REPO, VRO_DATA_TAG, and VRO_GIELLA_TAG
to point at a different release.
All path defaults are repo-local; override any with environment variables or a
local .env where the deploy script supports it.
Variable | Default | Description |
|
| Dictionary SQLite path used by |
|
| Corpus SQLite path used by |
|
| Word-bag SQLite path used by seen/unknown word checks. |
|
| Neurotõlge/TartuNLP translation API base URL. |
|
| Command used for GiellaLT morphological analysis. |
|
| Command used for one-analysis GiellaLT form generation. |
|
| Command used for token spellchecking. |
|
| Command used for sentence grammar checking. |
|
| Model path used by |
|
| Model path used by |
|
| Speller archive path used by |
|
| Grammar checker archive path used by |
|
| Maximum spelling suggestions returned per unknown token. |
|
| GitHub repository used for dataset and Giella release downloads. |
|
| GitHub release tag fetched for |
|
| GitHub release tag fetched for |
|
| Temporary build directory for |
|
| Output directory for locally built Giella artifacts. |
|
| Secret hosted HTTP path segment for Modal; local stdio clients do not need it. |
|
| Modal deploy data source: |
|
| Set to |
|
| Local data directory used when |
|
| Set to |
|
| Set to |
|
| Modal app name used by deploy/undeploy scripts. |
|
| Modal Volume name for SQLite data and Giella artifacts. |
|
| Modal secret name storing |
Point a client at it
You don't run the server yourself. The MCP client launches the vro-mcp-server
binary and talks to it over stdio, so all a client needs is the binary's
absolute path. Run make local-url to print that path and ready-to-paste config
for Claude Code and Codex.
Claude Code:
claude mcp add vro -- /absolute/path/to/vro-mcp-server/.venv/bin/vro-mcp-serverCodex:
codex mcp add vro -- /absolute/path/to/vro-mcp-server/.venv/bin/vro-mcp-serverGeneric JSON MCP client configuration:
{
"mcpServers": {
"vro": {
"command": "/absolute/path/to/vro-mcp-server/.venv/bin/vro-mcp-server",
"cwd": "/absolute/path/to/vro-mcp-server"
}
}
}Deployment
To host the server in the cloud so Claude or ChatGPT (the web apps) can reach it, see DEPLOY.md.
License
Code is MIT (LICENSE). The SQLite datasets are CC-BY-SA-4.0 and the prebuilt
GiellaLT models are GPL-3.0. Both are distributed as separate release assets,
each bundling its own license and attribution. See NOTICE.md for scope
and source summaries.
This server cannot be installed
Maintenance
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