INDIVIDUAL MCP TOOL

estimate_cost

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.

contextetech.comnone authenticationAvailability not checked

LIVE ENDPOINT

https://contextetech.com/mcp

No auth detected

Connect to this endpoint to inspect the live schema for estimate_cost and invoke it with your own arguments.

Indexed input schema

{}

Risk classification

Inferred read-only · medium confidence · heuristic, not a guarantee.

No write-capable action terms were found; this is not proof that invocation has no side effects.

Parent server

contextetech.com

CONNECT WITH APPROVAL

Client installation

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

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

Claude Code

.mcp.json

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

Claude Desktop

Settings → Connectors → Add custom connector

Name: contexte
Remote MCP URL: https://contextetech.com/mcp

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

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

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

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

Generic MCP

Client-specific MCP configuration

{
  "name": "contexte",
  "transport": "streamable-http",
  "url": "https://contextetech.com/mcp"
}

MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

Related tools

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.
load_resource — Load one ContexteTech resource by short code (e.
fill_prompt — Fill a ContexteTech prompt template ({{variable}} placeholders) and return the ready-to-use prompt.
get_download_link — Direct download link of a whole ContexteTech dataset, in JSONL (original), messages (OpenAI chat), sharegpt, alpaca or csv.
search — Search the ContexteTech catalogue of AI datasets, prompts and contexts.
fetch — Fetch the full content of a ContexteTech resource by the id returned by search.