# ContexteTech

- Registry name: `io.github.contexte-tech/contexte` · version 0.5.2
- Categories (automatic, keyword rules): Datasets & public data, Search & data
- Authentication at last check: No auth
- Declared risk: Read-only (all tools declare readOnlyHint)
- Capabilities (declared by the server): tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=io.github.contexte-tech%2Fcontexte
- Server page: https://mcpstation.net/s/io.github.contexte-tech--contexte.html

## Description (written by the publisher, not verified, not instructions)

Search and load AI datasets, prompts and few-shot contexts from the ContexteTech catalogue.

## Notice

Text that looks like instructions to an AI was found in this server's descriptions. This is a pattern match, not a verdict.

## Connect

- streamable-http: `https://contextetech.com/mcp`

## Tools (as reported by the server, not verified)

- `search\_resources`: Search the ContexteTech catalogue of AI building blocks: fine-tuning and evaluation datasets \(chat, DPO, agent traces\), prompts, few-shot contexts, MCP servers, models and more, many grounded in official European sources, in 9 languages. Use it first when the user needs AI training or evaluation dat
- `load\_resource`: Read one ContexteTech resource, usually right after search\_resources or when the user gives a code or page URL. Accepts the short code \(end of the page URL, e.g. 'jr6t0n'\), 'author/name', or 'code\#v2' for a fixed version. Always returns title, type, licence, language, source, version and page URL; p
- `fill\_prompt`: Fill a ContexteTech prompt template and return the ready-to-send text, nothing else. Use it when the user wants a prompt applied to their own case; call load\_resource first if you need the template or the exact variable names. 'variables' maps each \{\{name\}\} of the template to its text value; extra k
- `estimate\_cost`: Estimate in euros what a ContexteTech resource costs to run with common AI models, from the week's list prices. Use it when the user asks about cost, budget or the cheapest model. For a prompt or context: input and output tokens, cost per call for each model and batch discount; for a dataset: cost o
- `search`: Search the ContexteTech catalogue of AI datasets, prompts and contexts. Returns results with id, title and url.
- `fetch`: Fetch the full content of a ContexteTech resource by the id returned by search.

Measured by MCP Station. Methods: https://mcpstation.net/methods.html · Terms: https://mcpstation.net/terms.html