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130,857 tools. Last updated 2026-05-07 17:07

"Enhancements for Claude Desktop App with Large Contexts and Long Documents" matching MCP tools:

  • FOR CLAUDE DESKTOP ONLY (with filesystem access). For Claude.ai/web: Use create_upload_session instead - it provides a browser upload link. Upload local media to cloud storage, returning a public HTTPS URL. WHEN TO USE: • Instagram, LinkedIn, Threads, X: REQUIRED for local files before calling publish_content • TikTok: NOT NEEDED - pass local path directly to publish_content SUPPORTED FORMATS: • Images: jpg, png, gif, webp (max 10MB) • Videos: mp4, mov, webm (max 100MB) Returns { url: 'https://...' } for use in publish_content mediaUrl parameter.
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  • DESTRUCTIVE: Permanently delete an app, its Docker service, volume, and all data including version history. This cannot be undone. You MUST confirm with the user before calling this tool.
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  • Get app installation status and log. Poll this after install_app() to track progress. Requires: API key with read scope. Args: slug: Site identifier app_id: App ID from install_app() response Returns: {"id": "uuid", "app_name": "forge", "status": "running"|"installing"|"failed", "install_log": "..."} Statuses: "installing", "running", "stopped", "failed", "uninstalled"
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  • Query SEC filings and financial documents from US capital markets and exchanges. This tool searches through 10-K annual reports, 10-Q quarterly reports, 8-K current reports, proxy statements, earnings call transcripts, investor presentations, and other SEC-mandated filings from US companies. Use for questions about US company financials, executive compensation, business operations, or regulatory disclosures. Limited to official SEC filings and related documents only.
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  • Discover AXIS install metadata, pricing, and shareable manifests for commerce-capable agents. Free, no auth, and no mutation beyond read access. Example: call before wiring AXIS into Claude Desktop, Cursor, or VS Code. Use this when you need onboarding and ecosystem setup details. Use search_and_discover_tools instead for keyword routing or discover_agentic_purchasing_needs for purchasing-task triage.
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  • List all available Pine Script v6 documentation files with descriptions. Returns files organised by category with descriptions. For small files use get_doc(path). For large files (ta.md, strategy.md, collections.md, drawing.md, general.md) use list_sections(path) then get_section(path, header).
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Matching MCP Servers

  • F
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    Enables Claude Code to send prompts to Claude Desktop using macOS automation and AppleScript. Supports conversation management and configurable response polling, though reading responses back is limited by Electron's accessibility APIs.
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  • F
    license
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    quality
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    maintenance
    Enables Claude Desktop to interact with PostgreSQL databases through natural language for schema exploration, data analysis, and query execution. Users can search schemas, describe tables, and perform read or write operations without needing to write manual SQL.
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Matching MCP Connectors

  • Share context and questions between Claude instances — VS Code, claude.ai web, and mobile.

  • App Store and Play downloads and charts over time, Android uses bundle ID. Free key at trendsmcp.ai

  • Extract text from PDFs and images as clean Markdown. Uses Mistral OCR — handles complex layouts, tables, handwriting, multi-column documents, and mathematical notation. Preserves document hierarchy in structured Markdown. 10 sats/page. Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='extract_document' and quantity=pageCount for multi-page PDFs.
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  • Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use workspace.search for that.
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  • Upload local contexts to the GitWhy cloud as private (not shared with team). Use after saving contexts locally to back them up to the cloud. Synced contexts remain private until explicitly published with gitwhy_publish. CLI alternative: `git why push <context-id>` (syncs specified contexts as private).
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  • Edit a file in the solution's GitHub repo and commit. Two modes: 1. FULL FILE: provide `content` — replaces entire file (good for new files or small files) 2. SEARCH/REPLACE: provide `search` + `replace` — surgical edit without sending full file (preferred for large files like server.js) Always use search/replace for large files (>5KB). Always read the file first with ateam_github_read to get the exact text to search for.
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  • Comprehensive air quality assessment for a location in one call. Combines nearby monitor discovery and current readings with DAQI into a single response. Use this as the first tool call for any air quality question about a location. For long-term trend analysis, use the dedicated `trend_analysis` tool. Returns a structured 'summary' dict with purpose-appropriate sections. Present the summary description to users first. Args: location: Postcode, place name, or "lat,lon". purpose: What the user needs — "general" (default), "health" (safety/worry), "exercise" (outdoor activity), or "planning" (homebuying/school assessment/long-term).
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  • Browse regulatory documents with filters and pagination. Returns a paginated list of documents with summaries, tags, doc_purpose (regulation_text, enforcement, reference, irrelevant), and doc_jurisdictions (e.g. ['eu'], ['fi'], ['de']). Use this for filtered browsing (e.g. all DORA documents from the last 30 days). Use search_regulations instead when you have specific keywords to search for. Args: source: Filter by data source code: eur_lex, eba, esma, eiopa, finfsa, bafin. regulation: Filter by regulation family code: dora, mica, aml, mifid2, crd_crr, psd, csrd, sfdr, ai_act, emir, solvency, idd, gdpr. entity_type: Filter by entity type: credit_institution, payment_institution, e_money, investment_firm, fund_manager, aifm, insurance, pension, crypto_service, crowdfunding, credit_servicer. urgency_max: Max urgency level (1=critical, 2=high, 3=medium, 4=low, 5=informational). E.g. 2 returns only critical and high urgency items. days: Only return documents from the last N days (1-365). page: Page number (default 1). per_page: Results per page (default 20, max 100).
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  • Returns this server's runtime configuration: upload endpoint URL, output file TTL, file size limits, and base64 encoding rules. Call this before working with large files (≥ 4 MB) or when building multi-step workflows that chain tool outputs.
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  • Search UK companies with flexible filters. Combine name search, postcode, status, incorporation date range, SIC/GICS/ICB codes, accounts category, and company type. Returns enriched results with all SIC codes, GICS/ICB mappings, and address details. Cursor pagination for large result sets.
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  • Estimate token count + USD cost for a text across every major LLM (GPT-4o, GPT-4o-mini, o1, o1-mini, Claude 3.5 Sonnet/Haiku, Claude 3 Opus, Gemini 1.5 Pro/Flash, Llama 3 70B/8B) in one call. Returns per-model: estimated tokens, context-window fit %, input cost, and roundtrip cost (input+output). Also returns the cheapest and costliest model that fits. Use this before sending a long context to decide which model to route to. One call replaces 11 separate tokenizer lookups.
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  • WHEN: developer wants to improve code quality before a PR merge or code review. Triggers: 'refactor', 'clean up', 'simplify', 'too long method', 'nested ifs', 'code smells', 'améliorer le code'. Suggest concrete refactoring actions for YOUR custom D365 F&O X++ code. [!] Only runs on custom/extension code (D365_CUSTOM_MODEL_PATH). Refactoring standard Microsoft code is not actionable. Analyzes: long methods (extract method), deep nesting (guard clauses), row-by-row operations (set-based), large switch statements (strategy pattern), hardcoded strings (constants), unprotected CLR calls (error handling), wide transactions (narrow scope). Returns before/after code examples.
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  • 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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  • Analyze a URL for security threats (synchronous, blocks until complete or timeout). Returns risk score, confidence, agent access guidance, and intent_alignment (always not_provided for this tool; use url_scanner_scan_with_intent for intent context). For long-running scans, prefer url_scanner_async_scan which returns immediately with a task_id for polling via url_scanner_async_task_result.
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