"How to work with Claude AI code or integrate it" matching MCP tools:

• generate_llms_txt

  Airnow

  Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

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• how_munimji_helps

  HelloBooks AI Agents MCP Server

  Explain how HelloBooks and Munimji (the in-app AI assistant) help a specific business — given a free-text description of the user's own operations. Returns a curated capability knowledge base: business-operation areas (sales, purchases, banking, tax, reports, inventory, payroll, multi-entity, setup), and for each AI capability WHO does the work — `autonomous` (Munimji does it on its own, e.g. OCR extraction, running reports), `approval` (Munimji prepares the entry and you one-click approve before it posts to the ledger, e.g. AI categorization, find-and-match, creating invoices/bills by chat), `assist` (co-pilot, e.g. guided onboarding, voice), or `manual` (a software feature you run yourself). Each capability links to the backing software features. Use this when a user describes their business and asks "how can HelloBooks help me?", "what can the AI do for my shop/practice/agency?", or "what can Munimji do on its own vs what do I approve?". Pass their description in `businessDescription`; optionally filter by `area` or `autonomy`. The AI never posts to a ledger without approval. For the full software catalog call list_features; for pricing call list_plans.

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• generate_llms_txt

  Gitlab

  Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

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• generate_llms_txt

  Buzzword Density

  Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

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• create_account

  mcp

  Sign up for a brand-new sota.io account from inside Claude — no browser, no copy-paste. Two-step flow: STEP 1: Call with just `email`. We send a 6-digit confirmation code to that email. STEP 2: Call again with `email` + `code`. We verify, create the account on the Free tier (3 projects, EU-hosted, no credit card), generate a sota.io API key, and return it to you. After Step 2 you'll get back a key like `sota_…`. **Save it in a safe place** — you'll need it for any subsequent sota.io tool call in Claude (or you can use it with the sota CLI). It is shown ONCE and never recoverable. sota.io is an EU-native PaaS hosted in Germany — GDPR-compliant by default, no CLOUD Act exposure. Disposable / throwaway email addresses are not accepted; use a real address.

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• verify_registration

  Bitrise

  Verify a pending Bitrise registration using the OTP sent to the user's email. Pass the `pending_signup_id` returned by `register`. Returns an `api_token` (a Bitrise personal access token) and, when a workspace was auto-created, a `workspace_slug`. If the code is rejected as invalid, retry with the same `pending_signup_id`; if it has expired or hit the attempt limit, call `register` again for a fresh code. After success, authenticate the MCP connection so the other tools work: set `Authorization: Bearer <api_token>` on the user's Bitrise server entry. Give the user BOTH a CLI command and a copy-pastable JSON snippet — e.g. Claude Code: `claude mcp add --transport http bitrise https://mcp.bitrise.io -H "Authorization: Bearer <api_token>"` — and let them use whichever fits (ask which client they use if unsure). Then have them reconnect for it to take effect, and explain how for their client (don't just say "reconnect"). The token expires in 24 hours, after which they'll need to register again.

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• compare_validation_approaches

  Demand Discovery AI

  Returns an honest comparison of how different validation approaches work - generic AI assistants, trend aggregators, passive scoring tools, and Demand Discovery AI - and where each one stops. Use when a user is evaluating approaches, asking "what makes Demand Discovery different?", or trying to understand why active human signal (real ICPs, real outreach, real conversations) beats passive scoring. Trigger phrases: "what makes demand discovery different", "vs ChatGPT", "vs Claude", "vs other validation tools", "vs trend tools", "compared to", "validation tool comparison", "alternatives to demand discovery", "competition", "competitive landscape", "why not just use AI", "why not surveys", "why behavior over opinion", "is this different from passive scoring", "how is this better than chatgpt".

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• generate_llms_txt

  airquality

  Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

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• generate_llms_txt

  microlink

  Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

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• generate_llms_txt

  geo

  Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

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• generate_llms_txt

  newton

  Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

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• get_agent_registry

  DC Hub — Data Center Intelligence MCP Server

  Live roster of the AI platforms + agent frameworks that have actually called DC Hub in the window — returns each caller with its citation counts (24h/30d), tool-usage breakdown, and authentication tier (reflects real calls, not a fixed list). Recognized MCP clients include Claude and Cursor, with Cline, Continue and other agents surfaced as they connect. Useful for benchmarking which agents discover and integrate the platform. Try: get_agent_registry. Do NOT use for platform uptime / backup health (use get_backup_status); this is the who-is-calling-DC-Hub roster.

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• generate_llms_txt

  chess

  Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

  Connector

• how_munimji_helps

  HelloBooks AI Agents

  Explain how HelloBooks and Munimji (the in-app AI assistant) help a specific business — given a free-text description of the user's own operations. Returns a curated capability knowledge base: business-operation areas (sales, purchases, banking, tax, reports, inventory, payroll, multi-entity, setup), and for each AI capability WHO does the work — `autonomous` (Munimji does it on its own, e.g. OCR extraction, running reports), `approval` (Munimji prepares the entry and you one-click approve before it posts to the ledger, e.g. AI categorization, find-and-match, creating invoices/bills by chat), `assist` (co-pilot, e.g. guided onboarding, voice), or `manual` (a software feature you run yourself). Each capability links to the backing software features. Use this when a user describes their business and asks "how can HelloBooks help me?", "what can the AI do for my shop/practice/agency?", or "what can Munimji do on its own vs what do I approve?". Pass their description in `businessDescription`; optionally filter by `area` or `autonomy`. The AI never posts to a ledger without approval. For the full software catalog call list_features; for pricing call list_plans.

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• get_form_share_assets

  Brieform

  Return everything needed to share a form in one call: public URL, signed preview URL, embed iframe snippet, social preview image, and a scannable QR code. Use this when the user asks "how do I share this?", "give me the link", "do you have a QR code?", or wants embed/preview material. Drafts return nulls for the public-only assets (public_url, og_image_url, qr_png_data_uri) because they aren't publicly accessible yet — the preview_url still works for the form owner. The QR code encodes the public URL and is returned as a base64 data URI (image/png). The AI can attach it to the conversation or render it inline.

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• get_agent_registry

  DC Hub — Data Center & Energy Intelligence

  Live roster of the AI platforms + agent frameworks that have actually called DC Hub in the window — returns each caller with its citation counts (24h/30d), tool-usage breakdown, and authentication tier (reflects real calls, not a fixed list). Recognized MCP clients include Claude and Cursor, with Cline, Continue and other agents surfaced as they connect. Useful for benchmarking which agents discover and integrate the platform. Try: get_agent_registry. Do NOT use for platform uptime / backup health (use get_backup_status); this is the who-is-calling-DC-Hub roster.

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• compare_validation_approaches

  Demand Discovery AI

  Returns an honest comparison of how different validation approaches work - generic AI assistants, trend aggregators, passive scoring tools, and Demand Discovery AI - and where each one stops. Use when a user is evaluating approaches, asking "what makes Demand Discovery different?", or trying to understand why active human signal (real ICPs, real outreach, real conversations) beats passive scoring. Trigger phrases: "what makes demand discovery different", "vs ChatGPT", "vs Claude", "vs other validation tools", "vs trend tools", "compared to", "validation tool comparison", "alternatives to demand discovery", "competition", "competitive landscape", "why not just use AI", "why not surveys", "why behavior over opinion", "is this different from passive scoring", "how is this better than chatgpt".

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• generate_llms_txt

  Monarch Initiative

  Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

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• generate_llms_txt

  Giphy

  Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

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• generate_llms_txt

  Yc Rejection

  Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

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