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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 of one pass over all rows and a fine-tuning estimate on rented GPUs (hours and offers); for a model: memory (VRAM) needed and GPU offers that fit. Returns available: false with a note when no estimate exists for that type.","inputSchema":{"type":"object","properties":{"code":{"type":"string","description":"Short code"}},"required":["code"]},"annotations":{"title":"Estimate the cost","readOnlyHint":true,"destructiveHint":false,"openWorldHint":true},"definitionHash":"cef151d6195660935863f9eea4294c0a6cdf46068aec876231ca4b2d9ee8a15a","schemaStatus":"valid","origin":"official-registry","observedAt":"2026-11-01T02:46:15.605Z","metadataTrust":"untrusted"},{"serverName":"io.github.contexte-tech/contexte","endpointFingerprint":"7a2dc8a4c256f6bcf64715195450fd8184ccce62d92db2dd0e85d38998acd694","name":"fetch","title":"Fetch (connector format)","description":"Fetch the full content of a ContexteTech resource by the id returned by search.","inputSchema":{"type":"object","properties":{"id":{"type":"string","description":"Resource id or short code"}},"required":["id"]},"annotations":{"title":"Fetch (connector format)","readOnlyHint":true,"destructiveHint":false,"openWorldHint":true},"definitionHash":"e236577e71125ec8ae2e534769560a397b7b9288cf0b7676bb22d924fb42c83e","schemaStatus":"valid","origin":"official-registry","observedAt":"2026-11-01T02:46:15.605Z","metadataTrust":"untrusted"},{"serverName":"io.github.contexte-tech/contexte","endpointFingerprint":"7a2dc8a4c256f6bcf64715195450fd8184ccce62d92db2dd0e85d38998acd694","name":"fill_prompt","title":"Fill a prompt","description":"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 keys are ignored. Fails with an error if the code is unknown, if the resource is not a prompt, or if a template variable is missing (the error lists the missing names).","inputSchema":{"type":"object","properties":{"code":{"type":"string","description":"Short code of the prompt"},"variables":{"type":"object","description":"Values for each {{variable}}","additionalProperties":{"type":"string"}}},"required":["code","variables"]},"annotations":{"title":"Fill a prompt","readOnlyHint":true,"destructiveHint":false,"openWorldHint":true},"definitionHash":"ad3836f1d82379a9a272d1a626a5513c357c1831a08b68df6b2ef7db12a5227b","schemaStatus":"valid","origin":"official-registry","observedAt":"2026-11-01T02:46:15.605Z","metadataTrust":"untrusted"},{"serverName":"io.github.contexte-tech/contexte","endpointFingerprint":"7a2dc8a4c256f6bcf64715195450fd8184ccce62d92db2dd0e85d38998acd694","name":"load_resource","title":"Load a resource","description":"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; plus, for a dataset, the total number of rows, the first rows (default 10, max 50); for a prompt, the template and its {{variables}} (then call fill_prompt); for a context, the system prompt, knowledge and examples. The result ends with a Source line (resource, author, original data source, publisher, licence): citing it with its links is required. Fails with an error if the code does not exist or the resource is private.","inputSchema":{"type":"object","properties":{"code":{"type":"string","description":"Short code (end of the resource URL)"},"rows":{"type":"integer","description":"Dataset rows to return (default 10, max 50)"}},"required":["code"]},"annotations":{"title":"Load a resource","readOnlyHint":true,"destructiveHint":false,"openWorldHint":true},"definitionHash":"85b68885d120a0f3f060d745c22c2abc0bde335a55dd390e0be4ffb125b4b612","schemaStatus":"valid","origin":"official-registry","observedAt":"2026-11-01T02:46:15.605Z","metadataTrust":"untrusted"},{"serverName":"io.github.contexte-tech/contexte","endpointFingerprint":"7a2dc8a4c256f6bcf64715195450fd8184ccce62d92db2dd0e85d38998acd694","name":"search","title":"Search (connector format)","description":"Search the ContexteTech catalogue of AI datasets, prompts and contexts. Returns results with id, title and url.","inputSchema":{"type":"object","properties":{"query":{"type":"string","description":"Search words"}},"required":["query"]},"annotations":{"title":"Search (connector format)","readOnlyHint":true,"destructiveHint":false,"openWorldHint":true},"definitionHash":"0d3097b6cb0cf01334d0c5f7db58341fdd0a306a336f9e88c21bd8f125279120","schemaStatus":"valid","origin":"official-registry","observedAt":"2026-11-01T02:46:15.605Z","metadataTrust":"untrusted"},{"serverName":"io.github.contexte-tech/contexte","endpointFingerprint":"7a2dc8a4c256f6bcf64715195450fd8184ccce62d92db2dd0e85d38998acd694","name":"search_resources","title":"Search the ContexteTech catalogue","description":"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 data, a prompt, a context or an AI component, then call load_resource with a returned code. Write the topic in a few words, in English or the content language; common topics are matched across French, English, German and Spanish (e.g. 'marine weather' finds 'météo marine'), and a type word such as 'dataset' or 'prompt' puts that type first. Resources matching every topic come first; weaker matches carry match: partial. Returns up to 15 matches, each with short code, title, type, language, licence, author, rows (datasets), description and page URL; when nothing matches, returns a short message suggesting how to rephrase.","inputSchema":{"type":"object","properties":{"query":{"type":"string","description":"Search words, e.g. 'customs code' or 'GDPR'"},"type":{"type":"string","description":"Optional type: dataset, prompt, context, tool, model, agent, eval, rag…"},"language":{"type":"string","description":"Optional content language: fr, en, es, de, it, nl, pt, sv, pl"}},"required":["query"]},"annotations":{"title":"Search the ContexteTech catalogue","readOnlyHint":true,"destructiveHint":false,"openWorldHint":true},"definitionHash":"9edde46a9f3dbc93cbfda45544c7343144faecf5cb6dfad0471860e72d4f5a4a","schemaStatus":"valid","origin":"official-registry","observedAt":"2026-11-01T02:46:15.605Z","metadataTrust":"untrusted"}],"endpoints":[{"endpointFingerprint":"7a2dc8a4c256f6bcf64715195450fd8184ccce62d92db2dd0e85d38998acd694","protocol":"streamable-http","status":"indexed","toolCount":6,"observedAt":"2026-11-01T02:46:15.605Z"}],"authentication":"unknown"},"connectionConfigurations":{"status":"ready","authentication":"not embedded","clients":{"Claude Desktop":{"mcpServers":{"io.github.contexte-tech/contexte":{"url":"https://contextetech.com/mcp"}}},"Cursor":{"mcpServers":{"io.github.contexte-tech/contexte":{"url":"https://contextetech.com/mcp"}}},"VS Code":{"servers":{"io.github.contexte-tech/contexte":{"type":"http","url":"https://contextetech.com/mcp"}}}}},"resourceType":"mcp-server","callable":true,"runtime":{"callable":true,"protocols":["mcp"]},"interfaces":[{"protocol":"mcp","transport":"streamable-http","url":"https://contextetech.com/mcp"},{"protocol":"mcp","package":"contexte","registryType":"pypi","version":"0.5.1"}],"profile":{"apiVersion":"1","schemaVersion":"1","id":"mcp-server:io.github.contexte-tech%2Fcontexte","resourceType":"mcp-server","canonicalUrl":"https://www.agentsjunction.com/api/v1/servers/io.github.contexte-tech%2Fcontexte","name":"io.github.contexte-tech/contexte","description":"Search and load AI datasets, prompts and few-shot contexts from the ContexteTech catalogue.","interfaces":[{"protocol":"mcp","transport":"streamable-http","url":"https://contextetech.com/mcp"},{"protocol":"mcp","package":"contexte","registryType":"pypi","version":"0.5.1"}],"capabilities":[],"identity":{"source":"official-registry","websiteUrl":"https://contextetech.com/en/","repositoryUrl":null,"version":"0.5.2"},"verification":{"state":"official","confidence":100},"operations":{"resourceType":"mcp-server","name":"io.github.contexte-tech/contexte","status":"online","lastCheckedAt":"2026-11-03T18:17:10.612Z","lastSuccessfulCheck":"2026-11-03T18:17:10.612Z","latencyMs":301,"consecutiveFailures":0,"isStale":false,"checks":{"endpointReachable":true,"protocolValid":true,"agentCardValid":null,"mcpHandshakeValid":true},"lastSeen":null,"lastSuccessfulInteraction":null,"lastHealthCheck":"2026-11-03T18:17:10.612Z","source":{"type":"health-check","url":null},"observedAt":"2026-11-03T18:17:10.612Z"},"security":null,"timestamps":{"createdAt":"2026-10-15T20:40:48.353Z","updatedAt":"2026-10-15T20:40:48.353Z","observedAt":"2026-11-03T18:17:10.612Z"},"compatibility":{"serverVersion":"0.5.2","protocolVersions":[{"protocol":"mcp","version":null}]}}}}