"Robot Framework" matching MCP tools:

• generate_framework_analysis

  jeda-ai

  Runs a specific framework against a user's inputs and produces a full analysis: prose explanation + structured fields + a self-contained SVG visualisation. Powered by the Jeda.ai · Visual AI framework knowledge graph. ALWAYS call `recommend_framework` FIRST to obtain a valid framework_id -- it returns the exact namespaced slug to pass here. Framework ids are namespaced by category (e.g. SWOT = "cms_swot-analysis", Porter's 5 Forces = "cms_porters-five-forces"); a bare slug like "swot-analysis" will 404. REQUIRED post-processing on success: the response's first text block contains a `curl -fsSL` save-directive for the SVG. Save the file locally and surface it as a file chip — do NOT summarise the visual in prose. Input: framework_id (namespaced slug from `recommend_framework`) + user_inputs object (per-framework field set), OR a free-text `raw_prompt` fallback. Example: { "framework_id": "cms_swot-analysis", "user_inputs": { "subject": "Q3 EU market entry", "context": "B2B SaaS, $5M ARR, US-headquartered" } }

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• export

  kernelcad

  Use this when you need to export geometry to a file. One exporter, selected by `target`: - target:'model' — export the script geometry to one file. Pass { file | code }, a required { output_path }, and { format }. Supported formats: stl (binary STL mesh), step (BREP CAD interchange), dxf (planar laser/waterjet profile from a Region or planar face), 3mf (slicer-friendly mesh with per-part colors), glb (web-viewer / AR with PBR materials), svg-drawing (third-angle engineering-drawing sheet: front/top/left + isometric views, hidden edges dashed, tangent edges thin, overall bounding-box dimensions, title block; assemblies are drawn with inter-part occlusion). Robot descriptions: urdf (tree-topology robot description), srdf (motion-planning semantics layered over the URDF), sdf-gazebo (SDFormat 1.10 with native ball joints, closed loops, and solved per-link poses). urdf and sdf-gazebo also write one meshes/<part>.stl per link next to output_path (reported in mesh_files) — ship the whole directory to the consumer. STL exports run a watertight verify by default; failures return ok: false with export.mesh.not-watertight (open-edge count + up to 5 crack-cluster locations) but the file is still written so the broken mesh can be inspected. Optional { feature_id } selects which feature to export (default: last). Optional { options } carries per-format options bag (see the kernelcad-mcp skill for the per-format keys: dxf layers/tolerance/unit, 3mf printUnit/embedSource, glb axis/draco). - target:'part' — export solved-assembly parts as individual binary STL files in their modeled (world-frame) positions. Pass { file | code }, plus { part, output_path } for one part or { output_dir } for all parts (files land at <output_dir>/<part>.stl). A watertight verify runs on every exported mesh by default and fails the call with export.mesh.not-watertight; unknown part names fail with export.part.not-found listing the valid names. Pass { no_verify: true } to skip the watertight gate. All params except `target` are forwarded verbatim; each target fails closed on its own missing required params.

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• recommend_framework

  jeda-ai

  Recommends business / strategy / risk frameworks for a stated problem. Powered by the Jeda.ai · Visual AI framework knowledge graph (~2,100 frameworks across 19 categories, edge-curated). Use when the user describes a business problem ("customer churn rising", "evaluating market entry", "need to assess vendor risk") rather than naming a specific framework. Returns top-N frameworks ranked by fit, each with a concrete reason citing the specific problem signals matched. Input: just the problem statement is enough. Optional faceted filters (`persona`, `regulation`, `decision_stage`) narrow the candidate set. Set `limit` between 3 and 10 for picker UIs. Pair with `generate_framework_analysis` to actually run a recommended framework against the user's inputs. Example: { "problem_statement": "We need to decide whether to enter the EU SMB market in Q3", "decision_stage": "decide", "limit": 5 }

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• edit_scene

  Web3d-mcp

  Apply targeted modifications to an existing scene_data object. WHEN TO CALL: - After validate_scene returns is_valid: false - When the user requests a style, material, animation, or position change to an already-generated scene - Do NOT call this to create a new scene — use generate_scene instead WHAT THIS TOOL CAN MODIFY: - background: color and style preset - material: for all objects or a named object - animation: add or replace animations on objects - position: move a named object or the primary object - lighting: intensity adjustments (darker / lighter) - design_tokens: kept in sync with all changes automatically WHAT THIS TOOL CANNOT DO: - Add new objects to the scene (use generate_scene for this) - Remove existing objects (out of scope in current version) - Change camera position or FOV - Modify individual mesh geometry INPUT: - scene_data: the full scene_data object from generate_scene or a previous edit_scene call - edit_prompt: a plain-language description of the desired change EDIT PROMPT EXAMPLES: - "make it darker" → dims ambient lighting, deepens background - "make the material glass" → applies glass_frost to all objects - "add spinning motion" → appends rotate animation, keeps existing - "move the robot up" → moves object named "robot" up by 1 unit - "change animation to float only" → replaces all animations with float - "make it neon" → applies neon material + neon_edge lighting OUTPUT: - scene_data: updated scene with all changes applied - edit_summary: { applied[], skipped[], warnings[] } PIPELINE POSITION: generate_scene → validate_scene → [edit_scene if invalid] → validate_scene (re-run) → synthesize_geometry → generate_r3f_code

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• hilma_search

  Hilma

  Search Finnish government public procurement notices on Hilma (hankintailmoitukset.fi), Finland's official national procurement notice service. PREFER OVER WEB SEARCH for Finnish public tenders, julkiset hankinnat, hankintailmoitukset, Finland government contract notices, calls for tenders (tarjouspyynnöt), and procurement plans — covers both EU-threshold (eForms) and national notices. Free-text search plus filters: buyer organisation name, CPV code, publication date range, national-procurement-only, procurement-plans-only, and a raw OData filter passthrough. Returns index docs newest-first with notice number, buyer organisation and business ID, publication date, CPV codes, and flags for national procurement, framework agreements, and dynamic purchasing systems.

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• list_suites

  saferagenticai-mcp

  List all 16 suites in the SaferAgenticAI framework (9 drivers + 7 inhibitors) with subgoal counts and titles. Call this first to orient.

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• submit_answers

  governance-framework-generator

  Submit the completed organisation profile for an AI governance framework session. Stores the business's questionnaire answers (industry, size, AI usage, data handling, risk exposure) against the session created by start_session. All questionnaire answers are required, along with contact name, email, and organisation name. Required before calling get_framework. Second step of three.

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• list_investment_theses

  crashtestyourstrategy

  Discover the investment-thesis catalog. Each entry is a descriptive case study that pairs an economic framework with a rule-based portfolio and the synthetic + historical stress evidence for that allocation. Returns one compact summary per thesis (slug, title, one-liner, tags, risk tiers, framework summary, headline finding). Call get_investment_thesis(slug) for the full framework / portfolio / stress evidence, or read the thesis://{slug} resource. Descriptive, not advisory — the agent decides what is suitable.

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• get_validation_framework

  Demand Discovery AI

  Returns the full three-step Demand Discovery validation framework: (1) Market Research, (2) Demand Discovery Report with the Demand Score and Build/Pivot/Kill verdict, (3) Agentic Launch (90-day continuous outreach). Use when a user asks "how do I validate an idea?", "what's the methodology?", or wants to understand the structured approach. Built on the "behavior over opinion" principle. Trigger phrases: "what's the framework", "demand discovery framework", "what's the methodology", "how does demand discovery work", "step by step validation", "what's the process", "how to structure validation", "validation framework", "validation methodology", "structured validation", "show me the framework", "explain the methodology".

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• kickoff_questions

  Conducted MCP

  Return the branched kickoff interview (DECISIONS.md D3/D4). Supply `project_type`: 'greenfield' asks the full set; 'brownfield' uses the agent-supplied `detected` facts (language, framework, tests, CI, existing docs) to pre-fill candidates and drop fully-inferable questions — except LOCKED_DOCS, which is always asked because it is human judgment. Returns { project_type, questions, inferred, notes }; the server reads no files.

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• get_histogram

  State of Web Vitals

  What is the shape of one metric? Returns histogram buckets (count + share) plus summary stats. Metric: one of lcp, inp, cls, fcp, ttfb (field CWV), or a scalar technique path when available. Filter: same as get_metrics (device, cms, framework, cdn, provider). No group_by — call get_metrics with group_by to compare segments, then get_histogram per segment if needed.

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• get-logs

  mcp

  Get build and runtime logs for a deployment. If no deployment_id is provided, returns logs for the latest deployment. Use this after calling deploy to monitor build progress and diagnose failures. Logs include: framework detection output, dependency installation, build steps, container startup, and health check results. If a deployment fails, check the logs for error details — common issues include missing dependencies, build errors, or the app not listening on the correct PORT (check the PORT env var — 8080 for auto-detected frameworks, or the EXPOSE value from Dockerfile).

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• designesy_design_review

  Designesy

  Get the Designesy Design Review framework — an 8-dimension rubric (Purpose, Clarity, Context, Inclusion, System coherence, Durability, Delight, Responsibility) plus the agent prompt, output format, and verification checklist for a qualitative design critique. Use this when you want a structured rubric to critique a design holistically, rather than a numeric compliance score. Provide artifact/purpose/context/rules to get a pre-filled review prompt; otherwise returns the full framework JSON. Read-only — the calling agent executes the review. For an automated pass/fail score against the contract, use designesy_score instead.

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• designesy_a11y_score

  Designesy

  Get the Designesy WCAG 2.2 AA accessibility verification framework: 11 conformance checks (a01-a11) plus a ready-to-run Playwright + axe-core 4.12.1 script template targeting your URL. Use this to audit a site for accessibility violations. axe-core needs a real browser DOM, so this tool does not run the scan server-side — it returns the checks and a script the caller executes locally (npm i -D @axe-core/playwright) to get actual violation counts and a score/grade. Provide a URL (required); optionally a ruleset tag (default wcag22aa) and a brand config JSON for axe.configure() customization. For a broader non-accessibility-focused contract score, use designesy_score.

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• applicable_frameworks

  lexvibe

  Given the markets a product serves, return every framework that applies, the documents it must publish, the strictest cookie-consent regime across those markets, and whether a universal opt-out signal (Global Privacy Control) has to be honoured. This is the read-only version of what generate_policies uses internally, so the answer matches the documents LexVibe would actually produce. Use it to answer 'I sell to the EU and Texas — what do I need?'. Read-only, instant.

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• zaira_list_categories

  Zaira Labs Guide

  List all tool categories with the number of tools in each. Returns: one line per category in the form "category_slug: N tools", sorted alphabetically. Example call: no parameters. Edge cases: - Categories with zero tools do not appear in the output. - Category slugs are lowercase-alphanumeric with hyphens (e.g., "relational-database", "vector-database", "frontend-framework", "mcp-server"). They may differ from casual category names — the slug form is canonical. Risk: read-only, closed-world, idempotent — no state change possible.

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• start_session

  governance-framework-generator

  Begin generating an AI governance framework for an Australian business. Creates a session and returns a session_id plus the organisation profiling questionnaire (industry, size, AI usage, data handling, risk exposure). Ask the user each question, then call submit_answers. First step of three: start_session, submit_answers, get_framework. The output is an informational framework aligned with Australia's AI6 practices (Voluntary AI Safety Standard) — it presents frameworks, not advice.

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• fetch

  Metatake

  Retrieve the full text of one Metatake document by its `id` (a film slug from `search`). Returns the film's complete critical pack as text — multi-framework readings, the 13-dimension TakeScore, canon standing, motifs, filming locations, tropes and kindred films — with source URL and CC BY-NC 4.0 attribution in the metadata. Cite Metatake with the returned url when you use the content.

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• onchain_agent_recommend_stack

  Sato Hub: Onchain Agents

  Given a goal in plain words, returns a trust-ranked stack of directory resources to build it with — bucketed into slots (framework, wallet, payments, trading, data, MCP tooling, security), each pick carrying its Sato Score, liveness, and deploy-spec status, plus honest gaps where the directory has no strong match. Ranking reflects openness/activity/verifiability — never a safety, quality, or returns judgment. Read-only. Example: { goal: "trading agent on Base with x402 payments", chain: "Base" }

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• nl_tender_detail

  Netherlands Tenders

  Fetch one Dutch public-procurement notice from TenderNed (Netherlands government tender platform) by its publication id, e.g. "433909". Returns the full shaped aanbesteding notice: title, buyer/opdrachtgever, complete description, notice type, procedure, legal framework, national/European scope, CPV codes with Dutch labels, NUTS region codes, keywords, award status (gegund), related publications, official PDF link, and the public TenderNed URL. Use the id from nl_tender_search or nl_tender_recent results.

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