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667,158 tools. Updated 2026-10-16 23:33

"Resources for Building Agentic AI" matching MCP tools:

  • core.verifyA

    deep-agentic-core-mcpB

    Checks connectivity to agenticlens, agentic-chaos, agentic-sidecar, and ai-operations-spec, and reports readiness. Detects unreachable services to prevent workflow failures.
    MIT

  • agentic_statusA

    mastyf-aiC

    Retrieve overall status of agentic AI features, including metrics, scheduler, and task queue. Monitor the health of your AI infrastructure at a glance.
    AGPL 3.0

  • get_splunk_documentationA

    MCP Server for SplunkB

    Retrieve any Splunk documentation by URI pattern, including cheat sheets, troubleshooting guides, SPL references, and admin guides. Converts MCP resources into embedded content for agentic frameworks.
    Apache 2.0

  • create_agentic_workflowA

    NowAIKitC

    Create structured agentic workflows for ServiceNow AI agents by defining ordered steps, actions, inputs, and optional trigger conditions. Link workflows to a parent agent using its system ID.
    Elastic 2.0

Matching MCP Servers

  • mcp-resources-giulia-ai

    wganalytics
    A
    license
    Not graded
    quality
    C
    maintenance
    MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.
    MIT

  • agentic-hil

    agentic-hil
    A
    license
    A
    quality
    A
    maintenance
    Agentic Hardware-in-the-Loop (Agentic HIL) lets coding agents develop firmware on real embedded boards: flash, reset, read UART and exchange CAN traffic, diagnose and fix. Local, policy-gated MCP tools support OpenOCD, pyOCD and STM32CubeProgrammer, with pytest for CI.
    44
    890 PyPI
    18
    Apache 2.0

Matching MCP Connectors

  • agentic-ai

    Deal intelligence for agents: SEC-verified financials, validation, institutional deal scoring.

  • Pink Agentic AI Payments

    Pink Agentic AI Payments: AI agents pay within spending rules (budgets, caps, approval). Sandbox.

  • list_knowledgeA

    santismm-knowledgeA

    Get a complete list of knowledge units on agentic and enterprise AI, each with slug, category, title, summary, and Evidence-First provenance for easy browsing.
    MIT

  • list_patternsA

    santismm-knowledgeA

    Browse the full catalogue of enterprise AI patterns, with slug, category, name, summary, and provenance. Use search when looking for a pattern that solves a specific problem.
    MIT

  • list_architecturesA

    santismm-knowledgeA

    Browse enterprise agentic blueprints by listing reference architectures with id, slug, category, summary, and provenance. Use to explore options, not for specific use cases.
    MIT

  • list_governanceA

    santismm-knowledgeA

    List AI governance units—regulations, standards, frameworks, playbooks—with IDs, slugs, categories, names, and summaries. Use to browse rules before searching specific obligations or controls.
    MIT

  • score_agentic_browsingA

    automatelab-ai-seoA

    Score any webpage against Google's Agentic Browsing signals: llms.txt, WebMCP, accessibility-tree integrity, and layout stability. Get an overall 0-100 score and per-factor breakdown to evaluate AI agent readiness.
    MIT

  • get_building_breakdownA

    cenogram-mcp-serverA

    Breaks down a transaction's building sums into individual buildings, giving footprint, storeys, floor area, and construction-age estimates. Use after a search for detail.
    MIT

  • switch_modeA

    Inistate MCP ServerA

    Switch between configure, runtime, and frontend modes to access different tool sets and resources for module design, entry management, or custom UI development.
    Apache 2.0

  • relay_runA

    RelayPlaneA

    Execute a single AI model call to test prompts before building full workflows. Returns output, token usage, estimated provider cost, and trace URL.
    MIT

  • varity_agent_infoA

    Varity MCP ServerA

    Displays complete configuration details for an AI agent template, including resources, environment variables, cost, and access modes. Helps developers verify prerequisites before deployment.
    MIT

  • process_agentA

    docuprox-mcpA

    Submit a document file for synchronous agentic extraction. Uploads the file, waits, and returns extracted data directly—no job polling required.
    MIT

  • get_my_scopeA

    Alephant MCPA

    Retrieve the current virtual key scope, usage limits, and accessible resources for your AI API key.
    ISC

  • get_blueprintA

    Agent BlueprintA

    Retrieve a blueprint summary by ID, including title, executive summary, agentic pattern, platform, agent roles, and phase overview.
    MIT