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8 clients · secrets stay placeholders

JSON (mcpServers)Claude CodeCodexOpenCodeCursorVS CodeGemini CLIGoose

{
  "mcpServers": {
    "contexte": {
      "type": "http",
      "url": "https://contextetech.com/mcp"
    }
  }
}

claude mcp add --transport http contexte https://contextetech.com/mcp

[mcp_servers.contexte]
url = "https://contextetech.com/mcp"

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "contexte": {
      "type": "remote",
      "url": "https://contextetech.com/mcp",
      "enabled": true
    }
  }
}

{
  "mcpServers": {
    "contexte": {
      "type": "http",
      "url": "https://contextetech.com/mcp"
    }
  },
  "deeplink": "cursor://anysphere.cursor-deeplink/mcp/install?name=contexte&config=eyJ0eXBlIjoiaHR0cCIsInVybCI6Imh0dHBzOi8vY29udGV4dGV0ZWNoLmNvbS9tY3AifQ%3D%3D"
}

{
  "servers": {
    "contexte": {
      "type": "http",
      "url": "https://contextetech.com/mcp"
    }
  }
}

{
  "mcpServers": {
    "contexte": {
      "httpUrl": "https://contextetech.com/mcp"
    }
  }
}

extensions:
  "contexte":
    enabled: true
    name: "contexte"
    type: streamable_http
    uri: "https://contextetech.com/mcp"
    timeout: 300

Quality 92 / 100new

protocol100 · weight 25

pass
protocol.modernsupports 2026-07-28 (server/discover)
pass
protocol.statelessanswers without a session
pass
protocol.transportstreamable HTTP
pass
protocol.list_ttltool list is cacheable (ttlMs 3600000)

authorizationn/a · weight 15

n/a
auth.prm, auth.as_metadata, auth.cimdno remote uses OAuth
n/a
auth.secret_in_urlno templated URL

tool hygiene86 · weight 30

pass
tools.descriptionsevery tool has a description
pass
tools.description_lengthdescriptions are concise
pass
tools.schemasevery tool has an object input schema
pass
tools.annotations6 of 6 tools declare readOnlyHint or destructiveHint
fail
tools.directory_hintsno tool declares all four of readOnlyHint, destructiveHint, idempotentHint and openWorldHint; missing: search_resources (idempotentHint); estimate_cost (idempotentHint); fill_prompt (idempotentHint); …
pass
tools.token_costabout 1,157 tokens to load every tool
pass
tools.api_dumptools are not a one-to-one API dump

stabilityn/a · weight 15

n/a
stability.changes, stability.rug_pulltool history recorded for 4 of the 7 days needed

dependenciesn/a · weight 15

n/a
deps.known_vulns, deps.mcp_sdk_version, deps.resolvabledeps.dev does not know [email protected]

6 tools, about 1,157 tokens to load them all · tool set 0344ded30693 · tools last changed 2026-10-17 · checked 2026-10-19 20:38 UTC

Tool changes

2026-10-17get_download_linkremoved
Direct download link of a whole ContexteTech dataset, for when the user wants the full file (this online server does not write files); to only look at a few rows, use load_resource instead. Formats: jsonl (original), messages (OpenAI chat), sharegpt, alpaca, csv. Returns the URL, format, number of rows, licence, source and page URL. Fails if the code is unknown or the resource is not a dataset.
2026-10-17load_resourcechangeddescription
before
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) and a download URL; for a prompt, the template and its {{variables}} (then call fill_prompt); for a context, the system prompt, knowledge and examples. Fails with an error if the code does not exist or the resource is private.
after · 86% of words in common
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.
2026-10-17search_resourceschangeddescription
before
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, rows (datasets), description and page URL; when nothing matches, returns a short message suggesting how to rephrase.
after · 99% of words in common
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.
2026-10-16estimate_costchangeddescriptionmeaning changed
before
Estimated cost of a ContexteTech resource with common AI models (euros): input and output tokens, cost per call or per pass, batch discount, cheapest model; for a dataset, fine-tuning on a rented GPU.
after · 41% of words in common
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 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.
2026-10-16get_download_linkchangeddescriptionmeaning changed
before
Direct download link of a whole ContexteTech dataset, in JSONL (original), messages (OpenAI chat), sharegpt, alpaca or csv.
after · 30% of words in common
Direct download link of a whole ContexteTech dataset, for when the user wants the full file (this online server does not write files); to only look at a few rows, use load_resource instead. Formats: jsonl (original), messages (OpenAI chat), sharegpt, alpaca, csv. Returns the URL, format, number of rows, licence, source and page URL. Fails if the code is unknown or the resource is not a dataset.
2026-10-16fill_promptchangeddescriptionmeaning changed
before
Fill a ContexteTech prompt template ({{variable}} placeholders) and return the ready-to-use prompt.
after · 21% of words in common
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).
2026-10-16load_resourcechangeddescriptionmeaning changed
before
Load one ContexteTech resource by short code (e.g. 'jr6t0n'). Dataset: description, licence and the first rows; prompt: template and variables; context: system prompt and examples.
after · 27% of words in common
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) and a download URL; for a prompt, the template and its {{variables}} (then call fill_prompt); for a context, the system prompt, knowledge and examples. Fails with an error if the code does not exist or the resource is private.
2026-10-16search_resourceschangeddescriptionmeaning changed
before
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. Returns for each match: short code, title, type, language, licence, number of rows (datasets), description and page URL.
after · 41% of words in common
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, rows (datasets), description and page URL; when nothing matches, returns a short message suggesting how to rephrase.
2026-10-15fetchchangedannotations
2026-10-15searchchangedannotations

Showing the latest 10. Full history: list_changes · trend: quality JSON.

Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed. How it is computed.

Trust 80 / 100

no-repository

provenance45

liveness100

freshness100

hygiene80

+website +reachable +uptime-100% +updated-4d-ago -no-repository

Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed. How it is computed.

Dependencies

[email protected] PyPIthis version is not known to the dependency resolver

Dependency graphs from deps.dev; advisories from OSV.dev, including the GitHub Advisory Database and the PyPI Advisory Database; all CC BY 4.0. The graph is what a clean install of this version resolves today; nothing was installed or run. How it is checked.

Endpoints

remote	auth	reachable	uptime 30d	p50	protocol	last ok
`https://contextetech.com/mcp` streamable-http	none	yes	100%	421 ms	2026-07-28, 2025-11-25, 2025-06-18, 2025-03-26, 2024-11-05	2026-10-19

package	registry	version	runtime	secrets
`contexte`	pypi	0.5.1	uvx

Tools (6)

`estimate_cost`read-only	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 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.
`fetch`read-only	Fetch the full content of a ContexteTech resource by the id returned by search.
`fill_prompt`read-only	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).
`load_resource`read-only	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.
`search`read-only	Search the ContexteTech catalogue of AI datasets, prompts and contexts. Returns results with id, title and url.
`search_resources`read-only	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.

Schemas: list_tools.

Similar MCP servers

Official server.json

{
  "name": "io.github.contexte-tech/contexte",
  "title": "ContexteTech",
  "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
  "remotes": [
    {
      "url": "https://contextetech.com/mcp",
      "type": "streamable-http"
    }
  ],
  "version": "0.5.2",
  "packages": [
    {
      "version": "0.5.1",
      "transport": {
        "type": "stdio"
      },
      "identifier": "contexte",
      "runtimeHint": "uvx",
      "registryType": "pypi",
      "registryBaseUrl": "https://pypi.org",
      "packageArguments": [
        {
          "type": "positional",
          "value": "mcp"
        }
      ]
    }
  ],
  "websiteUrl": "https://contextetech.com/en/",
  "description": "Search and load AI datasets, prompts and few-shot contexts from the ContexteTech catalogue."
}