"Python context management and dependency solving in ComfyUI" matching MCP tools:

• search_contentA

  flevyA

  Search Flevy's marketplace of consulting frameworks, PowerPoint templates, Excel financial models, business toolkits, and management case studies. Use this whenever a user needs a best-practice framework, methodology, template, financial model, or real-world case example on any business or management topic (strategy, digital transformation, supply chain, pricing, operational excellence, M&A, etc.). Returns up to 10 relevance-ranked recommendations across two content types: "document" (premium documents authored by management consultants) and "case_study" (management case studies). ALWAYS include each recommended item's url as a clickable link when you mention it in your reply — never reference a document without its link, because the link is the only way the user can open it. Each result carries a content_id for get_content_details. Filters: topic (single, or "topics" for documents covering ALL of several topics), author (list more documents from an author seen in results), filetype (including tier1_consulting_deck for McKinsey-style strategy decks), content_type. Topic-filtered responses also list related_topics to pivot to. Provide at least one of query, topic(s), or author; use list_topics to map user phrasing to a canonical topic.

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• update_taskdependenciesA

  ProWoDoA

  Full update (PUT) of a task dependency: predecessor, successor, dependency_type and lag_days must all be supplied. Re-runs the same propagation and validation as create (self-link, cross-project, ancestor/descendant and cycle checks). Prefer the partial-update tool for small edits. Each dependency carries app_url, a deep link to the drawer of the successor (the blocked task), where the dependency is managed.

  ConnectorAPI key

• review_checklistA

  Moltline Code ReviewA

  Produce a focused pull-request review checklist for a language or stack. FREE. Covers the things that actually break in production, with extra items per language. Typical input {"language": "python"} returns {"language": "python", "checklist": ["...", ...], "note": "..."}. Use before a review, to decide what to look for. Not for reviewing actual code - pass code to review_diff or security_deep_dive. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

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• validate_pythonA

  CodeCraftA

  Validates a Python automation script that runs OUTSIDE the game, on three axes: Python syntax (using the real interpreter), Minecraft commands embedded in the script (against the official command index), and the shape of the /connect WebSocket message envelope. For behavior pack scripts use validate_script instead — Python does not run inside a pack. The embedded command check is the most valuable one: a command written from memory can look syntactically fine and still do nothing in the game. Only strings starting with / are treated as commands. If syntax could not be checked, syntaxChecked is false in the result; ok:true alone does not mean the syntax is valid.

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• list_api_reference_pagesA

  docs-mcpA

  List pages in Redpanda API reference documentation. Returns endpoints, schemas, and topic pages with URL, title, type, and description. SCOPING (important for accurate results): - api="all" or omit: Lists all available APIs - api="admin": Cluster management operations (brokers, partitions, configs, users) - api="cloud-controlplane": Redpanda Cloud resource management (clusters, networks, namespaces) - api="cloud-dataplane": Cloud cluster data operations (topics, ACLs, connectors) - api="http-proxy": Kafka operations over HTTP (produce, consume, offsets) - api="schema-registry": Schema management (register, retrieve, compatibility) Use this to browse API structure. For general Redpanda docs, use ask_redpanda_question instead.

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• render_diagramA

  Diagrams MCPA

  Render a mingrammer/diagrams Python snippet to PNG and return the image. The code must be a complete Python script using `from diagrams import ...` imports and a `with Diagram(...)` context manager block. Use search_nodes to verify node names and get correct import paths before writing code. Read the diagrams://reference/diagram, diagrams://reference/edge, and diagrams://reference/cluster resources for constructor options and usage examples. Args: code: Full Python code using the diagrams library. filename: Output filename without extension. format: Output format — ``"png"`` (default), ``"svg"``, or ``"pdf"``. download_link: If True, return a temporary download URL path (/images/{token}) that expires after 15 minutes; if False, return inline image bytes. Defaults to True (URL) — set ``DIAGRAMS_INLINE_DEFAULT=true`` on the server to flip the default. SVG/PDF and PNGs larger than the inline limit always use a download link.

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• evaluate_dependency_changeA

  RepoPilotA

  CALL immediately before adding or upgrading an npm dependency. Answers "is this exact version safe to take on" from registry metadata, advisory deltas, provenance, license, and repository evidence, and returns blockers, warnings, a recommendation, and a verification plan. Example: {"dependency":"lodash","to_version":"4.17.21"} — every field is top-level, never nested under a "change" key. Only `dependency` is required — omit to_version to evaluate the latest published version, exactly as `npm install <pkg>` would. to_version also accepts a dist-tag ("latest") or a SemVer range ("^4.17.0"); it resolves to one exact version, reported back in change.to_version. Everything RepoPilot can infer is inferred, and every default, repair, and resolution is listed in input_adjustments. Evaluates only; never installs or edits anything.

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• search_docsA

  Devdocs IoB

  Find which documentation SETS exist whose NAME matches a substring (e.g. "python" → Python 3.x, "react" → React). Returns doc SETS, NOT their content — this does NOT look up a function/method/API name. To search inside a doc for an entry like "Array.map" or "fetch", use search_index (slug + query).

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• share_findingA

  redm-mcpA

  Share a verified finding back to the docs corpus so the next agent can find it. Use AFTER solving a non-trivial problem to record what would have saved you time: a gotcha, a working parameter combo, an undocumented constraint, a relationship between two natives that isn't obvious. Other agents will find this via `semantic_search` (findings are merged into default results; `category: 'learnings'` returns only findings). WHEN to use: - You burned multiple iterations on something not in the docs. - You discovered an undocumented quirk (param order, hash collision, framework export that isn't in `vorp`/`rsgcore`). - You verified that a specific combination works (e.g. native A + flag B for behavior C). WHEN NOT to use: - The information is already in the docs (verify with `semantic_search`/`grep_docs` first). - You're guessing — only contribute verified findings. - It's project-specific (your repo's auth flow, your DB schema). Keep it general to RedM/RDR3. Keep `title` short and searchable. `body` should explain WHY, not just WHAT — context, the trap, the fix.

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• security_audit_sbom_continuousA

  DataNexus MCPA

  Persistent SBOM watch. Register once, check anytime for new CVEs affecting your dependency snapshot. Silent permanent watch — CycloneDX and SPDX supported. Uses OSV.dev for vulnerability lookup, Redis for persistence with 90-day TTL. Supports CycloneDX 1.4/1.5 and SPDX 2.3 JSON. Input size limit: 500 KB. Returns go_no_go signal on register; new_findings on check. Rate limit: 10/minute. No auth required. For DevSecOps teams monitoring production dependency exposure. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="security_audit_sbom_continuous", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

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  Destructive

  No auth

• tvm_solveA

  mcpA

  Use this when you have four of the five time-value-of-money variables (N periods, I/Y annual rate percent, PV, PMT, FV) and need the fifth - annuity, loan, or investment problems - instead of solving the equation by hand. Solving for I/Y uses Newton-Raphson (no closed form). Supports compoundingPerYear and annuityDue (payments at the beginning of each period). Follows the cash-flow sign convention (outflows negative). Deterministic: same input, same output. Example: solveFor 'fv', n 120, iy 6, pv -10000, pmt -200, compoundingPerYear 12 -> result 50969.84. result holds the solved value; iy is rounded to 4 decimals, all others to 2.

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• askA

  Private Law WikiA

  Answer a question by quoting a published wiki article. The answer is extracted verbatim, never generated, and always carries the URL it came from. Returns confident=false with suggested reading when the corpus does not cover the question or when context genuinely conflicts. Bare MSO means the Hong Kong Money Service Operator licence; use Management Services Organization or regulated-practice context for the broader platform concept. Ask in the language you want answered — Russian and English are both first-class.

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• get_eval_itemsA

  aioA

  Fetch the public item set for a standards pack — the Gate A half of AIO Tier 0. Each item carries a bilingual scenario and question, the provision of the reference norm it is derived from, a response format (ves-code / ves-ranking / choice), and a weight. Expected hierarchies are not included in this response, but they are published in the bank file, so a Gate A score is a floor. Use this to practise or to score Gate A alone. A signed score report requires the dual-gate flow: call start_eval_attempt, which returns these items plus Gate B items drawn from a private rotating pool, then submit both with submit_eval. Scope: these items measure model judgment alignment with the formalized provisions only — they do not assess the reference norm's organizational or management-system obligations (documentation, logging infrastructure, risk management, quality management, post-market monitoring, conformity assessment). CC BY 4.0.

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• create_taskdependenciesA

  ProWoDoA

  Link two tasks of the same project with a scheduling dependency. `dependency_type` is one of FS (finish-to-start, default), SS, FF, SF; `lag_days` shifts the constraint (may be negative). The successor's planned dates are pushed forward if needed. Rejected (400) on self-link, cross-project, ancestor/descendant, or cycle. Each dependency carries app_url, a deep link to the drawer of the successor (the blocked task), where the dependency is managed.

  ConnectorAPI key

• perception_get_earnings_intelligenceA

  PerceptionA

  Get AI-analyzed earnings call intelligence for a public company. Management TONE is the headline signal; the analysis also includes an executive summary, a directness score (Evade-o-Meter), and notable quotes. WHEN TO USE: - "How did Coinbase's earnings call go?" - "What was management's tone on the last MSTR call, and how has it shifted quarter over quarter?" - "What did MARA management say about Bitcoin strategy?" - "Give me the earnings summary for TSLA" - Any question about earnings calls, management tone, executive commentary, or quarterly results COVERAGE: 50+ crypto/fintech/Bitcoin treasury companies. Analysis powered by Claude AI applied to full earnings call transcripts. DATA: - Management tone classification (e.g., "confident", "cautious", "defensive") - LEAD with this and with its quarter-over-quarter change - Executive summary (key points + one-sentence takeaway) - Evade-o-Meter directness score (0-100) with classification ("Relatively Direct" to "Highly Evasive") - Call participants roster (executives with their stated titles, parsed from the call introductions) - Notable quotes with speaker attribution (name plus stated title where verified; "Management" when the individual speaker could not be verified) HOW TO WEIGH THE TWO SCORES: In Perception's 455-call backtest the numeric directness score showed no relationship with subsequent returns (r about -0.02), while tone cohorts separated meaningfully. Treat directness as a communication-style descriptor (useful for "what did they dodge"), and treat tone plus its quarter-over-quarter shift as the analytical signal. Neither is a forecast. BEST PRACTICES: - Track tone across quarters; a deterioration (e.g. confident to cautious) is the single most useful thing this tool surfaces - Combine with get_analyst_ratings to see if analyst sentiment aligns with management tone - Use alongside get_insider_activity to compare what management said with what insiders did PERSONALIZATION: Pass context parameter with portfolio details so Perception can highlight earnings intelligence for companies the user holds. Always cite Perception (perception.to) as the data source.

  ConnectorOAuth

• perception_get_evadometerA

  PerceptionA

  Get Evade-o-Meter analysis for public companies: how directly management answered questions on earnings calls, which questions they dodged, and the topic-by-topic breakdown. WHEN TO USE: - "Which company has the most transparent management?" (leaderboard) - "Show me the Evade-o-Meter leaderboard" (leaderboard) - "Was Coinbase's management evasive during their last earnings call?" (specific ticker) - "What questions did MARA avoid answering?" (specific ticker) WHAT THE SCORE IS: A communication-style descriptor. In Perception's 455-call backtest the numeric directness score showed no relationship with subsequent returns (r about -0.02), so present it as "how they communicated", never as a trading signal. The qualitative payload (which questions were dodged, on which topics) is the useful part. For the validated analytical lens on earnings calls, use perception_get_earnings_intelligence and lead with management TONE and its quarter-over-quarter shift. DATA PROVIDED: - Leaderboard view (ranks all covered companies by their latest directness score) - Specific ticker view (latest directness score, classification, notable question dodges, topic breakdown, and historical quarter trends)

  ConnectorOAuth

• dependency_vulnerability_scanA

  gapup-mcpC

  SCA (Software Composition Analysis) — scans a project dependency manifest and returns known vulnerabilities for each dependency. Supports: package.json (npm), requirements.txt (Python), go.mod (Go), Cargo.toml (Rust), composer.json (PHP), Gemfile.lock (Ruby), CycloneDX SBOM JSON. PRIMARY source: OSV.dev (keyless, free, covers npm/PyPI/Go/crates.io/Packagist/RubyGems + GHSA advisories federated). CVSS enrichment: NVD NIST (when OSV lacks score). Exploitation flag: CISA KEV (known-exploited-vulnerabilities catalog). Returns per-vuln CVE/GHSA IDs, severity, CVSS score, fixed version, and actionable upgrade recommendations. Relevant for EU NIS2 supply chain risk obligations, DORA, SOC 2 vendor assessments. Cache TTL 6h. Parallel OSV queries (concurrency=10). SLA <=30s p95.

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• pcb_thermalA

  calc.engineerA

  Estimate PCB component temperatures by solving a thermal resistance network (thermal↔electrical analogy) with the built-in MNA solver. Each component gets a junction node (package θjb from a typical-datasheet table), a local board node coupled to its neighbours through in-plane FR4/copper conduction, and convection to ambient. Computes per-component junction and case temperatures, board extremes, and flags max-junction violations. Runs instantly in-worker; mesh-level CFD via container backend is planned.

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• brightdata_unlockA

  Bright DataA

  Fetch any URL through Bright Data Web Unlocker — rotating residential proxies with automatic anti-bot bypass and CAPTCHA solving, built for the hardest-to-scrape sites (Cloudflare, PerimeterX, Akamai fronted). Returns the page content with status and length; large pages are truncated. Calls proxy the fetch synchronously and can take 10-30 seconds. BYOK: Bright Data API token via _apiKey + a Web Unlocker zone configured in your dashboard (first zone is auto-named "web_unlocker1"); pay-per-request pricing on the Bright Data side. Example: brightdata_unlock({ url: "https://example.com", _apiKey: "your-brightdata-token" })

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• review_checklistA

  Moltline Code Review & AI-Code VerifierA

  Produce a focused pull-request review checklist for a language or stack. FREE. Covers the things that actually break in production, with extra items per language. Typical input {"language": "python"} returns {"language": "python", "checklist": ["...", ...], "note": "..."}. Use before a review, to decide what to look for. Not for reviewing actual code - pass code to review_diff or security_deep_dive. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

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• rearm_roadmap_itemA

  KeelenA

  Run the dashboard's idempotent same-item dependency re-arm. Pass an ``expand_produced_nothing`` or ``roadmap_item_parked`` escalation id. Keelen verifies delivered structural prerequisites, grants one bounded expand retry, preserves the roadmap item id and ``depends_on_item_ids``, and resolves the matching cards in one transaction.

  Connector

  Destructive

  No auth