MCP server

mindmelt – B2B agency Frankfurt Official

de.mindmelt/agency

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Read-only data on mindmelt, a B2B agency in Frankfurt: services, cases, pricing, fit checks.

Website

At a glance

Type

MCP server

Publisher

mindmelt.de (verified by the MCP Registry)

Status

Working at last check

Tools

8

Token cost

About 1,210 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http agency https://www.mindmelt.de/mcp/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.agency]
url = "https://www.mindmelt.de/mcp/mcp"

Gemini CLI

{"mcpServers":{"agency":{"httpUrl":"https://www.mindmelt.de/mcp/mcp"}}}

Cursor

{"mcpServers":{"agency":{"url":"https://www.mindmelt.de/mcp/mcp"}}}

VS Code

{"servers":{"agency":{"type":"http","url":"https://www.mindmelt.de/mcp/mcp"}}}

Antigravity

agy mcp add agency https://www.mindmelt.de/mcp/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"agency","server_url":"https://www.mindmelt.de/mcp/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"agency","server_url":"https://www.mindmelt.de/mcp/mcp"}

Tools

• check_fit ~152 tokens
  Freitextbasierter Abgleich einer Anforderung gegen die in selection-rules.json dokumentierten good_fit/poor_fit-Kriterien (signals) sowie services/capabilities. requirement: Freitext-Anforderung/Situationsbeschreibung des Interessenten. Gibt zurueck, ob/welche good_fit- bzw. poor_fit-Kr
• find_cases ~158 tokens
  Filtert cases.json nach industry-ID und/oder exaktem capability-Feld. industry: exakte oder teilweise industry-ID aus cases.json (z.B. "b2b-werbeagentur"). capability: Suchbegriff, der exakt gegen das capability-Feld jedes Case gematcht wird (kein Fallback auf das services-Array).
• find_pages ~255 tokens
  Durchsucht den vollstaendigen Seitenindex von mindmelt.de (pages.json, alle Sitemap-URLs inkl. Sub-Brands und englischer Version) ueber Title, H1, Meta-Description und URL. query: Suchbegriff(e), z.B. "Relaunch", "KI Schulung", "Healthcare". Leer = alle Seiten. sub_brand: mindmelt | min
• get_capability ~92 tokens
  Liefert einen einzelnen Eintrag aus capabilities.json anhand seiner id. id: capability-id, z.B. "seo" oder "webentwicklung".
• get_company_profile ~59 tokens
  Liefert entities.json organization + people gebuendelt (Firmenprofil).
• get_pricing ~222 tokens
  Liefert Preisinformationen aus pricing.json. sub_brand: filtert auf eine Sub-Brand, z.B. "mindmelt studio", "mindmelt speaker" oder "mindmelt" (optional, ohne Angabe werden alle Sub-Brands geliefert). id: liefert genau einen Eintrag anhand seiner id, z.B. "werbeagentur-website"
• recommend_services ~132 tokens
  Matched eine Problembeschreibung gegen die 'problem'-Felder in services.json und liefert die am besten passenden Services samt verknuepfter capabilities. problem: Freitext-Problembeschreibung, z.B. "B2B-Relaunch mit SEO und KI-Sichtbarkeit".
• search_services ~140 tokens
  Volltextsuche (Keyword/Alias-Matching, kein Vector-Search) ueber capabilities.json und services.json inkl. aliases aus entities.json. query: Suchbegriff(e), z.B. "SEO Relaunch" oder "KI Sichtbarkeit". Gibt sortierte Treffer aus capabilities und services mit Score zurueck.

Browse

• SEO
• Converting to Markdown
• Health and medicine

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