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523,718 tools. Updated 2026-09-06 13:58

"Testing Local AI Agents in LMStudio for Computer Use and Code Execution Tasks" matching MCP tools:

  • 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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  • Release active local Axint file claims for this agent after finishing or abandoning a task. This keeps parallel agents and Xcode from blocking each other on stale claims. Use: use after finishing or abandoning claimed files; use agent.claim before edits and agent.advice for next steps. Inputs: agentId releases only its matching claims unless files narrow the release set. Effects: updates local coordination claims under .axint/coordination; no network.
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  • Get Lenny Zeltser's IR one-page executive brief template. Standalone variant of `ir_get_template` for callers that only want the brief without the long-form report. This server never requests your incident notes and instructs your AI to keep them local—guidelines flow to your AI for local analysis.
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  • Get Lenny Zeltser's Vuln one-page executive brief template. Standalone variant of `vuln_get_template` for callers that only want the brief without the long-form report. This server never requests your vulnerability notes and instructs your AI to keep them local—the brief template and guidelines flow to your AI for local analysis.
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  • Get Lenny Zeltser's Security Assessment one-page executive brief template. Standalone variant of `assessment_get_template` for callers that only want the brief without the long-form report. This server never requests your assessment notes or report and instructs your AI to keep them local—the templates and guidelines flow to your AI for local analysis.
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  • Generate or regenerate AI agent profile avatar(s) for a company's AI team. Use when an operator wants to create, refresh, or restyle one or more agents' profile avatars. Single agent: pass agent_id OR agent_name. Several agents: pass agent_ids[] OR agent_names[] in ONE call. Whole team: pass all:true. The tool regenerates EVERY target itself in a single call (1 credit per agent) and returns the real new signed avatar_url for each. Report ONLY the agents listed in the result's `regenerated` array — never claim or invent an avatar for an agent the tool did not return. [sensitive-tier — first use may require a manager's approval; a from-now-on approval makes future calls seamless, a just-once approval re-asks next time.]
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Matching MCP Servers

  • A
    license
    B
    quality
    B
    maintenance
    Exposes Anthropic's computer-use action surface (screenshot, click, move, keyboard, clipboard, batch) against a persistent desktop display via MCP stdio protocol. Enables AI agents to control a virtual desktop environment through natural language instructions.
    24
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Provides a JSON-RPC computer use runtime for macOS, exposing 7 MCP tools (observe/act/inspect/session/cancel/trace) as image content blocks so external agents like Claude Code, Pi, OpenCode, or Codex CLI can capture screenshots and drive the desktop with clicks, keys, and typing while enforcing session locking, stale-frame protection, and trace redaction server-side.
    13
    1
    MIT

Matching MCP Connectors

  • Get Lenny Zeltser's expert writing guidelines for security reports and assessments. Provides guidance on tone, structure, clarity, executive summaries, and avoiding common writing mistakes. Includes rating-sheet items (the four lens sheets: structure, look, words, tone) as concrete reference points for grounded feedback. Works for any security document. This server never requests your documents and instructs your AI to keep them local—guidelines flow to your AI for local analysis. Note: For incident response reports specifically, use the ir_* tools which provide deeper section-by-section review criteria.
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  • Get Lenny Zeltser's CTI one-page executive brief template. Standalone variant of `cti_get_template` for callers that only want the brief without the long-form report. This server never requests your campaign or threat-intel notes and instructs your AI to keep them local—templates and guidelines flow to your AI for local analysis.
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  • Get Lenny Zeltser's one-page Vulnerability Advisory Brief template. Covers Bottom Line, Quick Facts, Are We Affected?, Defensive Actions (with What/Why/When/Who), What We Don't Know, and More Information. This server never requests your vulnerability notes and instructs your AI to keep them local—the brief template and guidelines flow to your AI for local analysis.
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  • AI Melody to Music — Upload a clean single-instrument recording and AI generates instrumental music in your style. No vocals — for songs with vocals, see AI Hum to Song or AI Song Generator.. 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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  • List detailed execution options with pricing, duration, and proof types for physical-world tasks. Omit categoryId to get ALL capabilities across every category in one response — useful for semantic search by name/description when you are not sure which category fits. Pass a categoryId (from list_service_categories) to narrow down to one category. Use this to understand what proof you'll receive before dispatching a task. No authentication required. Next: dispatch_physical_task.
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  • 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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  • Create multiple tasks in a project in one action. Use this instead of calling create_task multiple times when the user asks to create several tasks at once. All tasks are created atomically — if validation fails for any item, nothing is created.
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  • Retrieve the structured tasks and milestones for an idea, pulled from its Execution Playbook, Product Roadmap and/or First 100 Days simulation. Use the source parameter to pick one plan or get all of them merged. Read-only and free; use update_task to tick First 100 Days items off.
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  • Create a Gantt chart from a task list — no account or API key needed. YOU author the plan: list the tasks in execution order with realistic working-day durations and dependencies (0-based positions of earlier tasks; use { task, type, lag } for start-to-start/finish-to-finish links or lag). Milestones have duration 0. Only add a dependency where a task truly needs another one finished - independent tasks should run in PARALLEL (share a predecessor, or take no dependencies at all and start at the project start). Group tasks into top-level phases for a structured plan/WBS: the phase task gets isPhase: true, its tasks get parent = the position of the phase. LoopGantt schedules it with its critical-path engine and returns a picture of the chart, the dates, the critical path and a link where the user can view, export (PNG/PDF) and save the chart. Always show the user the link. Tasks with a due date take deadline: YYYY-MM-DD (a marker - the reply reports the fit). Use create_gantt when the user wants a chart to open, export or save; use schedule_project instead for what-if date math where nothing should be stored.
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  • AI Voice Cloner — Clone any voice from a short audio sample — upload a 5-10 second recording and generate speech in that voice. 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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  • AI Agent Tokenized Stock OS: list canonical tokenized stocks (Robinhood Stock Tokens), ETFs, USDG, and WETH on Robinhood Chain ID 4663. Use for AI agents trading tokenized equities/RWAs. Do NOT use for US brokerage equities (use Robinhood Trading MCP). Only registry addresses are real tokenized stocks.
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  • 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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  • Sign a serialized Solana transaction with the configured SAP MCP signer after sap_preview_transaction. This is the supported non-custodial signing path for agents; never read keypair JSON or sign raw message bytes in temporary scripts. SAP MCP execution guidance: Intent: SAP MCP tool workflow. Pricing: paid value-action; preview cost and transaction effects before user confirmation. Routing: hosted accountless write is blocked; do not call this as a paid hosted write and no x402 payment should be charged. Use sap_payments_finalize_transaction when user signing is required. Signer boundary: user-controlled local profile or external signer; OOBE hosted MCP remains non-custodial.
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  • The REAL all-in monthly cost per vendor for a decoder topic (slug from list_cost_decoders, e.g. 'ai-customer-support-cost'), computed in deterministic code from sourced, dated inputs — each vendor's per-seat price + AI billing model + per-unit price, totalled at named scenarios (e.g. 5 agents at 1,000 and 5,000 AI resolutions/mo) with the arithmetic shown. Quote-only inputs return a null total, never a fabricated number. Optionally pass agents + resolutions for a custom scenario. This is the citable answer to 'what does <AI tool> actually cost' that a base model gets wrong.
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  • Deterministically evaluates arithmetic, mathematical, and logical expressions inside an AST-isolated sandbox. Prevents LLM calculation errors while strictly blocking arbitrary code execution. Use for reliable numerical calculations and boolean logic. Do not use for executing arbitrary Python statements or importing external libraries.
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