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524,529 tools. Updated 2026-09-06 16:29

"Multi-agent AI systems for collaborative code development" matching MCP tools:

  • Get World Bank time-series data — economic, social, and development statistics — for ANY country worldwide (Spain, Brazil, Germany, Nigeria, Japan, etc.). PREFER for "unemployment rate in <country>", "<country> inflation rate", "GDP of <country>", "<country> population / life expectancy / poverty rate / CO2 emissions". Pass the ISO country code + a World Bank indicator code; common ones: GDP=NY.GDP.MKTP.CD, GDP per capita=NY.GDP.PCAP.CD, inflation=FP.CPI.TOTL.ZG, unemployment=SL.UEM.TOTL.ZS, population=SP.POP.TOTL, life expectancy=SP.DYN.LE00.IN, poverty rate=SI.POV.DDAY, literacy=SE.ADT.LITR.ZS. For CO2 use the dedicated country_co2_emissions tool (the old EN.ATM.CO2E.* codes were DELETED by the World Bank; the live series is EN.GHG.CO2.MT.CE.AR5). (Annual data — a national statistics office may have fresher monthly figures.)
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  • List canvas documents in a workflow run. Canvas documents are collaborative markdown files that multiple agents can edit in parallel. Omit run_id to list documents across all runs. Read-only. Use read_canvas for content and get_canvas_toc for section IDs. There is no get_run; list_runs returns run records. Pass playbook_id as the UUID or GUID of the playbook this call should target.
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  • Publish one public Markdown text post as a selected agent owned by the signed-in human operator. Use list_my_agents first to obtain the agent ID. Use the dedicated code tools for code requests and reviews; App and Cabana posts are not available through this connector release. Call only after the user explicitly confirms the exact title, body, tags, agent, and optional karma reward.
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  • Deterministic production-readiness gate for AI-built systems. Verifies the invariants that stop a system silently shipping broken: every critical component is PRESENT and LOADS, the import closure resolves (nothing assumed 'already on the box'), all runtime dependencies are declared, and health is a REAL fail-closed check. Returns approve/reject with a fix plan and ISO 27001 / ISO 5055 control evidence. Facts are gathered by the Verificate collector in your CI; the gate is the authority. Non-bypassable, fails closed. This is the control-plane sibling of validate_ai_output — code quality is one invariant; this gates the whole deployable.
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  • THE approval inbox for V2 rule automation — the ONLY surface for pending automation approvals (MinMax/AOE/scheduled-task tools are separate systems, not this inbox). status=pending (default) means NOT yet approved/dismissed by a user: pending_approval (manual queue + AI escalations), pending_ai_review, shadow (AI Shadow Mode — AI applied NOTHING; needs your approve/dismiss) and ai_rejected (overridable). Rows carry approval_mode (manual|ai_review|ai_shadow|auto), rule owner, needs, undoable, and paginate with total_found/truncated/next_offset. scope=mine (default) shows only the calling user's rules; scope=all_users shows every user's. READ-ONLY: action=list. Approving/rejecting/undoing inbox items lives in stage_automation_review.
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  • Decode an in-game GW1 skill template code (e.g. "OwpiMypMBg1cxcBAMBdmtIKAA") into professions, attribute allocations and the 8 skills with their stats and descriptions. Whitespace and line wraps in the pasted code are tolerated. This decodes a SINGLE build code; for a multi-hero paw-ned2 team blob, use decode_pawned_team instead.
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  • FEEDBACK: Submit feedback, bug reports, or feature requests to Luther Systems Use this tool to forward user feedback directly to the Luther Systems team. This includes bug reports, feature requests, questions, or general feedback about InsideOut. The agent itself can also use this tool to report issues it encounters during operation. REQUIRES: session_id, category, message OPTIONAL: user_email (for follow-up), user_name, source (default: 'mcp'), initiator ('user' or 'agent') Categories: bug_report, feature_request, general_feedback, question, security The 'initiator' field tracks who triggered the report: - 'user' — the user explicitly reported the issue or requested feedback submission - 'agent' — Riley detected an issue and initiated the feedback flow Examples: - User says 'the deploy button is broken' → submit_feedback(category='bug_report', message='...', initiator='user') - User says 'I wish it had dark mode' → submit_feedback(category='feature_request', message='...', initiator='user') - Deployment failed with Terraform error → submit_feedback(category='bug_report', message='Deployment failed: Terraform apply error on aws_alb resource — timeout waiting for ALB provisioning', initiator='agent')
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  • Returns every distinct code_type (e.g. CPT, MS-DRG) with catalogued cost data, along with each type's distinct code count and total hospital reports. Unpaginated. Use this to discover which code systems have data before drilling into list_codes.
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  • Returns Mastra (Bun) and LangGraph (Python) patterns for AI agent workflows. Call this BEFORE create_workflow / update_draft when building chatbots, tool-using agents, or multi-step LLM flows. Do not hand-roll custom agent loops — use the preinstalled frameworks.
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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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  • 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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  • Solve algebraic polynomial equations: quadratic equations (a*x^2 + b*x + c = 0) and 2-variable simultaneous linear systems (a1*x + b1*y = c1, a2*x + b2*y = c2) with exact real and complex roots. Behavior: Deterministic, idempotent calculation with zero external side effects. For quadratics: evaluates discriminant D = b^2 - 4*a*c; computes real roots or complex conjugates (x1, x2 = (-b ± i*sqrt(|D|)) / (2*a)), and parabola vertex coordinates. For simultaneous systems: evaluates Cramer's determinant rule (D, Dx, Dy) to solve unique solutions or identify singular/parallel systems. Usage Guidelines: Use when solving quadratic polynomials or 2-unknown linear systems. Do not use for statistical data fitting; use linear_regression instead.
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  • Return the canonical list of 26 ancient divination systems Mythsensus implements (slug, English + Thai name, region, required inputs). Use first when asked "what systems do you support?".
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  • Use this read-only tool when a business owner asks "How can AI help my business?", "Where do I start with AI?", or wants to understand AI strategy, workflow automation, business process improvement, AI readiness, tool selection, revenue opportunities, or brand-consistent AI systems. It explains TEK BOSS, the free result, and when the assessment is not appropriate. It never retrieves customer data.
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  • Propose a new/updated Idea note → Inbox. Title-match to update; send the COMPLETE revised text. Set resync:true ONLY when you rewrote the note FROM the current systems (get_stale lists notes the systems have moved past) — it stops the adopted note from immediately nagging to re-generate the systems it was just written from.
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  • Renders the current state of a live Trident document as a PNG image directly from the Yjs collaborative session — bypassing Firestore, which may be stale. Returns a base64-encoded PNG. Use this to visually verify that diagram edits look correct before or after making changes.
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  • FEEDBACK: Submit feedback, bug reports, or feature requests to Luther Systems Use this tool to forward user feedback directly to the Luther Systems team. This includes bug reports, feature requests, questions, or general feedback about InsideOut. The agent itself can also use this tool to report issues it encounters during operation. REQUIRES: session_id, category, message OPTIONAL: user_email (for follow-up), user_name, source (default: 'mcp'), initiator ('user' or 'agent') Categories: bug_report, feature_request, general_feedback, question, security The 'initiator' field tracks who triggered the report: - 'user' — the user explicitly reported the issue or requested feedback submission - 'agent' — Riley detected an issue and initiated the feedback flow Examples: - User says 'the deploy button is broken' → submit_feedback(category='bug_report', message='...', initiator='user') - User says 'I wish it had dark mode' → submit_feedback(category='feature_request', message='...', initiator='user') - Deployment failed with Terraform error → submit_feedback(category='bug_report', message='Deployment failed: Terraform apply error on aws_alb resource — timeout waiting for ALB provisioning', initiator='agent')
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  • Get quantitative parameters from knowledge entries. Use this for cross-domain consistency checking. Parameters include numeric values, units, and individual confidence levels. For example, you might check whether the total power budget in energy-systems is consistent with the compute power draw in ai-compute-infrastructure. Args: domain: Filter by domain slug (optional) parameter_name: Filter by parameter name substring (optional)
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  • Build an unsigned SOL transfer to support Blueprint development. Blueprint provides free staking infrastructure for AI agents — donations help sustain enterprise hardware and development. Same zero-custody pattern: unsigned transaction returned, you sign client-side. Suggested amounts: 0.01 SOL (thank you), 0.1 SOL (generous), 1 SOL (patron).
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  • Multi-source web search with automatic fallback chain: HackerNews Algolia → Wikipedia REST → DuckDuckGo → x711 Hive collective intelligence. Always returns results — if live web sources are unavailable, falls back to community-sourced agent knowledge from The Hive. Best for: tech/AI/crypto queries, current events, documentation discovery. Returns: { query: string, results: Array<{ title, url, snippet }>, source: string ('HackerNews'|'Wikipedia'|'DuckDuckGo'|'x711_hive'), count: number }. Free tier: 10 calls/day, no API key needed.
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  • List the 17 UN Sustainable Development Goals (code, title, description). Optionally drill into one goal to get its targets and indicators.
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