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650,501 tools. Updated 2026-10-13 22:52

"Python Object-Oriented Programming Resources" matching MCP tools:

  • Return the ENTIRE corpus including premium resource bodies in one document — the keyed deliverable of the Corpus/Enterprise license. Requires a Corpus- or Enterprise-tier api_key (a Starter key unlocks premium resources but NOT the corpus file); without an entitled key a payment-required/upgrade object is returned. The free, premium-stubbed version is get_corpus.
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  • Return the ENTIRE corpus including premium resource bodies in one document — the keyed deliverable of the Corpus/Enterprise license. Requires a Corpus- or Enterprise-tier api_key (a Starter key unlocks premium resources but NOT the corpus file); without an entitled key a payment-required/upgrade object is returned. The free, premium-stubbed version is get_corpus.
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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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  • Fetch a federal account's budget data: total obligations, gross outlays, and budgetary resources, plus the per-Treasury-Account-Symbol (TAS) component breakdown in children. Federal accounts connect appropriations law to actual agency spending. Account codes come from usaspending_search_federal_accounts (its account_number output field) or usaspending_get_award_federal_accounts (its federal_account field), and are formatted as AGENCY-MAIN (e.g., 097-0100 for DoD Operation and Maintenance). For obligations broken down by program activity or object class, use usaspending_get_federal_account_breakdown.
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  • List the env vars a project's code can use and the resources behind them: (1) resources CONNECTED to the project — usable as process.env.<NAME> in endpoint code now; (2) the owner's other account-level credentials — reusable, but not usable in code until connected; (3) everything Floot can add. Call it to learn what env vars exist before writing backend code, and BEFORE provisioning or requesting any credential (the owner may already have the one you need). Pass query (case-insensitive substring over names, descriptions, types, and env var names) to filter when the account has many resources. Read-only. Details: get_guides('resources').
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  • Run Python code from natural language prompts, with optional PyPI package install.

  • Hosted Python sandbox for package runtime verification: pip install and usable-import evidence.

  • List all 71 available programming languages and their IDs for code execution. Common IDs: 71=Python 3.8, 63=JavaScript (Node.js), 62=Java, 54=C++ (GCC), 60=Go, 73=Rust, 51=C#, 46=Bash. Returns full list with compiler/interpreter versions (Judge0 CE)
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  • 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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  • Fetch full AWS doc pages as markdown. `search_documentation` already returns verbatim page chunks, so don't re-read a URL whose chunk you already have to "confirm" or "round out" an answer -- the chunk is the real page text; treat it as authoritative. Reading the full page is justified ONLY when the chunks genuinely lack the content: - an enumeration or aggregation ("list all X", "how many X") needs the complete set and the chunks show only part of it; - no search result is on-topic after refining the query, and a known doc URL would have the answer. Otherwise, answer from the chunks. Use exact URLs from `search_documentation`; don't guess slugs. Input: `requests: [{url, max_length?, start_index?}]`. Batch 2-5. - `max_length` default 10000. - `start_index` default 0; use prior `end_index` to continue, TOC offset to jump. Allow-listed prefixes: docs.aws.amazon.com; aws.amazon.com (not /marketplace); repost.aws/knowledge-center; docs.amplify.aws; ui.docs.amplify.aws; github.com/{aws-cloudformation/aws-cloudformation-templates, aws-samples/{aws-cdk-examples, generative-ai-cdk-constructs-samples, serverless-patterns}, awsdocs/aws-cdk-guide, awslabs/aws-solutions-constructs, cdklabs/cdk-nag} (README on `main`); constructs.dev/packages/{@aws-cdk-containers, @aws-cdk, @cdk-cloudformation, aws-analytics-reference-architecture, aws-cdk-lib, cdk-amazon-chime-resources, cdk-aws-lambda-powertools-layer, cdk-ecr-deployment, cdk-lambda-powertools-python-layer, cdk-serverless-clamscan, cdk8s, cdk8s-plus-33}; strandsagents.com/latest/documentation/docs/; karpenter.sh/docs/; Amazon Braket: {amazon-braket-sdk-python, amazon-braket-schemas-python, amazon-braket-default-simulator-python, amazon-braket-pennylane-plugin-python, amazon-braket-algorithm-library, qiskit-braket-provider, autoqasm, qirtoqasm}.readthedocs.io and github.com/amazon-braket/* (blob/tree/raw). Output: SUCCESS -- markdown + `total_length, start_index, end_index, truncated, redirected_url?` (truncated includes TOC with char ranges). ERROR -- `error_code` in {not_found, invalid_url, throttled, downstream_error, validation_error}.
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  • Takes JSON that almost parses and makes it parse: markdown code fences, prose wrapped around the object, trailing commas, single or smart quotes, unquoted keys, Python True/False/None, comments, NaN, and brackets left open by a truncated response. Every change is reported, so the caller learns what its generator got wrong rather than silently depending on a fixer. When the input cannot be salvaged it returns the precise line, column and a caret pointing at the offending character — which is what makes the next attempt succeed instead of guessing.
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  • Lista os MCP Resources disponíveis com URI, nome e mime-type. Tools de descoberta para clientes que não expõem UI de attachment de resources (como o Claude.ai web). Em Claude Desktop / Cursor / MCP Inspector, resources aparecem em picker dedicado. Resources contêm dados de referência estáticos (tabelas de domínio, glossário, metadados do servidor). Use `compras_obter_resource(uri)` para ler o conteúdo. Retorno: { "total": int, "resources": [ {"uri": str, "nome": str, "descricao": str, "mime_type": str, "tags": [str,...]}, ... ] }
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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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  • Search curated AI/ML engineering roles for free. Filter by tags (e.g. llm, pytorch), workplace (remote/hybrid/onsite), global remote eligibility, experience level, salary range, or keyword. After selecting a role, candidates may use compile_job_specific_resume for a $0 transient ATS-oriented preview without identity; a verified key is required only to save an approval-bound artifact. The employer outcome pilot never affects organic results.
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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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  • [duvera · risk:low] Look up the current version, summary, license, and homepage of a Python package on PyPI. No account required.
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  • List every patient-side symptom in the Mediora catalog (fatigue, joint pain, headache, etc.). Returns slug + short name. Use mediora__explain_symptom for the full triage-oriented explainer including the lab work-up a clinician would order.
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  • PAID $0.002 (x402, USDC on Base). Coerce near-miss LLM JSON to a JSON-Schema-conformant object: strip code fences/prose, fix trailing commas/quotes/unquoted keys, normalise Python literals, balance brackets, then coerce types, apply defaults, and drop extraneous keys. Returns the repaired object OR precise per-field errors. Args: json (the raw string), schema (a JSON Schema object). Without payment returns the x402 challenge.
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  • Compile a $0 candidate-controlled ATS-oriented plain-text Markdown resume for one active job using only candidate-verified evidence. Without identity, returns a transient non-persisted preview that cannot be approved or submitted. With a verified candidate key, saves an immutable draft hash plus a machine-readable candidate_review handoff and requires the agent to pause for explicit human review. Never submits or authorizes an application.
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  • Run a short Python program in an isolated sandbox and get back exit code, stdout, stderr, duration and up to 3 artifact files from ./out/. Python 3.12 + numpy/pandas/requests, no network, 512 MB, 30 s max, 32 KB code, 4 input files of 256 KB. Free compile-only syntax check first at POST /api/v1/run-python/validate. $0.05/call (one run) via x402. Free syntax check: POST /api/v1/run-python/validate. Free worked example: GET /api/v1/run-python/example.
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  • Use this when the task calls for plain text files on a paired computer: source code, configuration, Markdown, logs, scripts, or other line-oriented text. Use read_document instead for PDF, DOCX, XLSX and other structured document content. read_file keeps legacy PDF/DOCX extraction for compatibility but should not be the model’s first choice for those formats.
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  • Get metadata for a Python package on PyPI (the Python Package Index). Returns the latest version, summary, author, license, project URLs, required Python version, keywords, classifiers, and the release artifact files that `pip install` would download. Pass the exact pip package name (e.g. "requests", "numpy").
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