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597,353 tools. Updated 2026-09-21 14:35

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

  • 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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  • Fast code search across any public git repo. Returns file paths, line numbers, and code snippets with context. Supports regex, boolean queries, fuzzy matching, and structural filters (declarations, usages, strings, comments). Dependency/build directories excluded by default. Searching for leaked secrets? Call code_analyze instead and read security_summary — it runs a real secret and credential scanner over the whole repository, where searching for key prefixes like "sk-", "ghp_" or "AIza" only matches the spellings you happened to think of.
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  • List the projects on your account (archived included), each with `id`, `slug`, `name`, `apiBaseUrl` and `archived`. Requires an ACCOUNT-scoped management token (one minted with no project) and the `read` scope. A PROJECT-scoped management token cannot call this: use it on its own project's tools instead.
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  • Mint a PROJECT-scoped management token (`er_mcp_`) for MCP and REST; it cannot authenticate relay traffic. Use it after create_project to configure a fresh project, or for any project you already own. Attenuated by design: the scopes must be a subset of THIS management token's own grant (`read` is always included), expiry is mandatory (1–90 days, default 30, never "never"), and the minted management token (being project-scoped) can never mint management tokens itself. `spend` is human-granted only: no management token, of any scope, can mint one carrying it. Mint a spend-scoped token from the project's panel instead. Requires an ACCOUNT-scoped management token and the `config` scope. Returns the plaintext exactly once; only its hash is stored.
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  • 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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  • 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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  • 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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  • 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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  • 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.
    ConnectorOAuth
  • 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.
    ConnectorOAuth
  • 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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  • 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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  • Ends the management relationship over an account you provisioned: you lose access to it, and its NIFs stop counting towards your billable usage from the next billing cycle. - **The holder:** keeps the account, its NIFs and its invoices, and becomes responsible for their own subscription. Nothing is deleted or anonymised. - **Reversible:** only while the account stays unclaimed. Provisioning the same email again reactivates it (see `POST /v1/accounts`), and only the manager who ended the relationship can do so. Once the holder claims the account it is theirs, and getting the management back needs their consent, not just their email address. - **Entitlement:** requires `manage_accounts`. Endpoint: DELETE /v1/accounts/{account_id}/management
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    Destructive
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  • Test a specific Python package/version on a supported Python/Linux target runtime using empirical execution. Returns scoped install evidence, usable-import evidence when requested, and a scoped result/receipt. Supported boundary: public PyPI on Linux x86_64 / CPython 3.13. This is not generic package advice, security verification, arbitrary Python execution, broad compatibility testing, feature behavior testing, or application integration testing.
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  • Scan pasted project files for known Vercel Python-runtime deploy footguns: conflicting requirements.txt/pyproject.toml manifests, a dependency manifest missing from the project root, sibling-module imports that need sys.path, multiple top-level ASGI apps under api/, streaming/SSE responses that can crash the Python runtime, oversized dependencies (torch/tensorflow/etc.), and unrouted .well-known/ files. Static analysis over file contents -- it doesn't run a real build, so a clean result means 'no known footgun found,' not a deploy guarantee. To scan a public GitHub repo automatically instead of pasting files, use the $29 checkout at https://www.edgethirteen.com/tools/vercelpycheck.
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  • Retrieve combined scores from all major sports leagues (NBA, NFL, NHL) in a single call. Returns games from all three leagues with final scores, teams, game times, and standings summaries. Use for comprehensive sports news monitoring or multi-sport fantasy management.
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  • Rename a project you own (the display name only: the slug, which identifies the project in URLs and API paths, never changes). Requires an ACCOUNT-scoped management token and the `config` scope. 404-equivalent error when you do not own the slug.
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    Destructive
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  • Use for qualitative company discovery (industry, business model, supply chain, competitors, management background). For numerical screening (revenue, margins, ratios, growth rates) use run_sql on company_snapshot instead. Drillr's company knowledge graph — searchable across industry classification, product offerings, business model, segment structure, competitive landscape, supply chain, management background, and customer profile. Coverage: US, Japan, Hong Kong, China A-shares, and Korea. `market` accepts one lowercase value or a list from `us | jp | hk | cn | kr`; omit it or pass `[]` for all five. List order does not set priority. Pass a natural-language description (for example, "Hong Kong and China EV battery suppliers"). Returns a structured list of matching companies with context snippets. ONLY for finding a LIST of companies by description.
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  • Retrieve the list of tables configured in the app, used for restaurant mode or table management.
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  • Return the verified implementation of an Owl Group Trading indicator in a given platform. Args: slug (e.g. 'rl10', 'dragon', 'river-flood-plain') and platform (e.g. 'python', 'javascript'). Returns the commented source code, the verification proof (real Python-vs-JS parity), the summary, and the page URL. Call list_indicators first to see valid slugs and platforms.
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