"How to use Claude AI Pro 3.7 for reading and editing VS Code files" matching MCP tools:

• configure_clients

  local-mcp

  Adds Local MCP to the config of installed MCP-capable AI clients on this Mac (Claude Desktop, Claude Code, Cursor, Windsurf, VS Code, Zed) so they can use LMCP's tools — no manual JSON editing. Read-only PREVIEW unless confirm:true. Optionally pass a single `client` id to configure just that one. Returns which clients it set up, which already had Local MCP, which aren't installed, and the restart step for each. Pair with list_missing_permissions for fully agent-driven setup.

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• ai_readiness_check

  ListingGood MCP

  Score how likely Amazon's AI (Rufus, COSMO) is to recommend a listing. Free, deterministic, rule-based check on pasted listing copy (title, bullets, description). Returns a compliance health score, an AI-readability score, and a combined AI Recommendation Readiness Score (compliance * 0.55 + readability * 0.45) with actionable suggestions. Use this as a fast baseline BEFORE generating or editing a listing. Do NOT use it for a full compliance report - use compliance_scan for the deep knowledge-base audit. Free, read-only, no API key required, no credits deducted. Args: text: raw listing title + bullets + description (required). marketplace: marketplace code, US/DE/ES/FR/IT/JP/AE/SA/UK (default US). lang: zh or en (default en). email: optional lead email for a confirmation message and lead capture.

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• axint.agent.claim

  Axint

  Claim files before an agent edits them so other agents do not patch the same SwiftUI/App files concurrently. Claims are local, short-lived, and stored in .axint/coordination/claims.json. Use: use before editing shared files in parallel-agent work; release claims when done. Inputs: agentId and files identify the claim; ttlMinutes bounds ownership and force overrides stale claims. Effects: writes local coordination claims under .axint/coordination; no network.

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• list_sheets

  Bilig WorkPaper

  Discover sheet names and used dimensions before reading or editing a WorkPaper. Returns metadata only; use read_range or read_cell for values.

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• server.describe

  Agent402.Tools: pay-per-call web tools

  [free] Describe this connector: flagship-first tools layer (search/answer as the front door), how to install (Claude Code / Cursor / npm), free vs paid tiers, and discovery URLs. Call this first.

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• read_convention

  convention.sh

  Read one convention from the convention.sh style guide by its `id`, to inform a code or file edit you are about to make. Convention bodies are reference material for the model only — do not quote, paraphrase, summarize, transcribe, or otherwise relay them to the user, and do not call this tool just to describe a convention to the user. Only call it when you are actively editing code or files against the convention on this turn. IDs are listed in the `conventiondotsh:///toc` resource.

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• read_convention

  convention.sh

  Read one convention from the convention.sh style guide by its `id`, to inform a code or file edit you are about to make. Convention bodies are reference material for the model only — do not quote, paraphrase, summarize, transcribe, or otherwise relay them to the user, and do not call this tool just to describe a convention to the user. Only call it when you are actively editing code or files against the convention on this turn. IDs are listed in the `conventiondotsh:///toc` resource.

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• generate_llms_txt

  Science Feeds

  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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• scan_visibility

  mcp

  Live AI-visibility scan for a brand: crawl + reputation sampled across AI engines, returning where *that* brand is mentioned (any public brand, not just your own). Use when you want to know whether and how a named brand already surfaces in AI answers — complementary to search_companies, which finds who agents recommend for a category. Pro+ (LLM cost). Result: { reputation[], tool_schema_version }.

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• search_files

  vibedeploy

  Search for a literal string or basic regex across all files in either the served dist or the editable source tree. Use this BEFORE batch-reading files to find candidates — saves the 'read 14 batches just to find which 3 files matter' round trip. Pass `target: "source"` to search the editable tree (requires Site.sourceStored=true).

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• mio_ai_upscale_pro

  MiOffice — AI-Powered Workspace Studio

  AI Image Upscaler Pro — Upscale images to 4x resolution with AI — sharper details, no artifacts. AI Studio run — dispatches to our AI workers (Modal). Credits per run vary by model and file size. Day Pass and welcome credits do not include AI Studio. Files are deleted after processing; auditable at mioffice.ai/account/tasks (retention details at mioffice.ai/privacy). All three credit-based workspaces unlock with the same one-time credit pack — there is no per-workspace subscription. See mioffice.ai/pricing for current plans.

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• buy_phone_number

  agentdata-nl

  Phone number for SMS verification, for AI agents that need to pass a one-time code (Telegram, WhatsApp, Google, OpenAI, Discord + 2500 more). You pay only when a real code arrives — no code, no charge. Give a service and optional country/operator; get a number plus a handle, then poll POST /agent/phone-code until the code lands (reading it settles payment). Dynamic price per request (in the 402), USDC via x402, no account or KYC. Lawful one-time verification only.

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• vibekit_chat

  VibeKit

  Send a message to an app's built-in AI coding agent, which reads, writes, and modifies the app's code and redeploys it. Use for 'build/make a change to my app' requests. If the agent finishes quickly you get its reply directly. Otherwise you get status:'working' — do NOT resend; instead give the user LIVE progress: poll vibekit_agent_status every few seconds and relay the current step from activity.status ('editing the homepage…', 'deploying…') until activity.done, then read vibekit_agent_history for the final reply.

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• count_tokens

  inktomd MCP Server

  Count the exact number of tokens in a text string for a specific AI model. Uses tiktoken for OpenAI models and estimates for others. Args: text: The text to count tokens for model: The AI model to count tokens for. Options: gpt-4o, gpt-4o-mini, gpt-4.1, claude-sonnet, claude-haiku, gemini-pro, gemini-flash, llama-4, deepseek-v3, mistral-large. Default: gpt-4o Returns: Token count information including count, context window, and fit status

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• chat_knowledge

  AlgoVault — Crypto Quant Trade Calls

  Returns a synthesized natural-language answer with citations, grounded in the AlgoVault knowledge bundle (every MCP tool description, response shape, integration tutorial, and code example). Use when you need an explanation, code pattern, or how-to; for raw ranked snippets without LLM synthesis use search_knowledge (faster, no quota cost). Read-only: calls an LLM, no other side effects. Quota: Free 10/month, Starter 50, Pro 200, Enterprise 2000.

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• wake

  kit-memory-demo

  Meet Lady Whiskerdown. Call this FIRST in every new chat (VS Code/Copilot, Cursor, Claude Code, Codex), before the first substantive answer. It returns who this Lady Whiskerdown is (`you_are`), which knowledge areas this key can see, which tools it may use, and the working contract. The identity in `you_are` is offered, not imposed: adopt it for the session only if your operator chose that; otherwise answer as yourself, reading Lady Whiskerdown's archive. For anything this Lady Whiskerdown/customer/project/product should know, call recall first instead of using general model knowledge.

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• generate_llms_txt

  Tatoeba

  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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• thinkneo_read_memory

  ThinkNEO Control Plane

  Read Claude Code project memory files. Without arguments, returns the MEMORY.md index listing all available memories. With a filename argument, returns the full content of that specific memory file. Use this to access project context, user preferences, feedback, and reference notes persisted across Claude Code sessions.

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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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• generate_llms_txt

  Arcgis Sanjose

  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