"Learning or Writing Code in Python" matching MCP tools:

• ateam_redeploy

  ateam-mcp

  Re-deploy skills WITHOUT changing any definitions. ⚠️ HEAVY OPERATION: regenerates MCP servers (Python code) for every skill, pushes each to A-Team Core, restarts connectors, and verifies tool discovery. Takes 30-120s depending on skill count. Use after connector restarts, Core hiccups, or stale state. For incremental changes, prefer ateam_patch (which updates + redeploys in one step).

  Connector

• search

  MedRates

  Search for medical procedure prices by code or description. Use this for direct lookups when you know a CPT/HCPCS code (e.g. "70551") or want to search by keyword (e.g. "MRI", "knee replacement"). For code-like queries → exact match on procedure code. For text queries → searches code, description, and code_type fields. Supports filtering by insurance payer, clinical setting, and location (via zip code or lat/lng coordinates with a radius). NOTE: Results are from US HOSPITALS only — not non-US providers, independent imaging centers, ambulatory surgery centers (ASCs), or other freestanding facilities. Args: query: CPT/HCPCS code (e.g. "70551") or text search (e.g. "MRI brain"). Must be at least 2 characters. code_type: Filter by code type: "CPT", "HCPCS", "MS-DRG", "RC", etc. hospital_id: Filter to a specific hospital (use the hospitals tool to find IDs). payer_name: Filter by insurance payer name (e.g. "Blue Cross", "Aetna"). plan_name: Filter by plan name (e.g. "PPO", "HMO"). setting: Filter by clinical setting: "inpatient" or "outpatient". zip_code: US zip code for geographic filtering (alternative to lat/lng). lat: Latitude for geographic filtering (use with lng and radius_miles). lng: Longitude for geographic filtering (use with lat and radius_miles). radius_miles: Search radius in miles from the zip code or lat/lng location. page: Page number (default 1). page_size: Results per page (default 25, max 100). Returns: JSON with matching charge items including procedure codes, descriptions, gross charges, cash prices, and negotiated rate ranges per hospital.

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• get_strategy_code

  quantifyme

  Get the actual Python code behind a community leaderboard strategy. Use after `browse_community`: pass an entry's `id` here to read its real `feature_engineering()` + `strategy_config()` source so the user can inspect or tweak it. To deploy it unchanged, pass the same id to `one_shot` as `community_id`. Read-only, no signup needed. Args: community_id: The `id` of a community entry (from `browse_community`). Returns: dict with: id, title, username, description, symbol, timeframe, metrics {total_ret, win_rate, profit_factor, n_trades, mdd, sharpe_strat}, and `code` (the full Python source). SHOW the code to the user, and offer to deploy it via one_shot(community_id=...) or tweak it first.

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• discovery_signup_verify

  Disco

  Complete Disco signup using an email verification code. Call this after discovery_signup returns {"status": "verification_required"}. The user receives a 6-digit code by email — pass it here along with the same email address used in discovery_signup. Returns an API key on success. Args: email: Email address used in the discovery_signup call. code: 6-digit verification code from the email.

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• find_examples

  Senzing

  Find working SOURCE CODE examples from 37 indexed Senzing GitHub repositories. REQUIRED: either `query` (string, for search) or `repo` with `file_path` or `list_files=true` — the call WILL FAIL without one. Three modes: (1) Search: pass `query` to find examples across all repos, (2) File listing: pass `repo` + `list_files=true`, (3) File retrieval: pass `repo` + `file_path`. Indexes source code (.py, .java, .cs, .rs) and READMEs — NOT build/data files. For sample data, use get_sample_data. Covers Python, Java, C#, Rust SDK patterns: initialization, ingestion, search, redo, configuration, message queues, REST APIs. Use max_lines to limit large files. Returns GitHub raw URLs for file retrieval.

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• tool_compute_sandbox

  agent-vending-factory

  POST /tools/tool_compute_sandbox/run — Executes Python 3.12 code in an isolated subprocess with a 5-second hard timeout. Input: {python_code: string, input_data: any (optional, bound as variable 'input_data')}. Output: {success, result, stdout (capped 50KB), execution_time_ms, error_type}. Return value: assign to 'result' variable. Pre-loaded: math, json, re, statistics, itertools, functools, collections, decimal, datetime, random, hashlib, base64. Blocked: import, open(), eval(), exec(), os, sys, network, class definitions, dunder attributes. error_type values: syntax_error | security_error | runtime_error | timeout_error. Cost: $0.1500 USDC per call.

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• list_strategy_tones

  Heista

  List tone profiles for a strategy. Today returns at most one entry — the tone_of_voice synthesized by the Tone of Voice Synthesis agent (POWER-mode bundles only). The shape is list-stable so future multi-tone bundles plug in without changing the contract. Use this to align generation with the brand-tied voice DNA before writing copy, hooks, or scripts.

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• vest_search_tools

  vest-mcp

  Search and browse AI tools available in Vest's cashback catalog. Returns names, slugs, categories, and live cashback rates. Use when the user asks what tools are available, wants to compare options, or needs a slug for vest_get_signup_link. Real triggers: 'what AI writing tools does Vest have?', 'show me coding tools with high cashback', 'find tools under $50/mo'. Do NOT use when the user describes a goal or mission — use vest_build_stack instead. Do NOT use to get a signup link — use vest_get_signup_link.

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• get_compression_candidates

  Push Realm

  Find clusters of related learnings that are ripe for compression. When many similar solutions get linked together (e.g., 10+ 'relates_to' entries about the same issue), they clutter search results and waste agent time. Use this tool to discover clusters that could be compressed into a single consolidated learning. WORKFLOW: 1. Call get_compression_candidates with min_cluster_size=3 (or higher) 2. Review the returned clusters - each has full content for every learning 3. Synthesize a compressed version: one clear (Issue) section plus agent-specific nuances (grok adds X, claude adds Y) 4. Call compress_learnings with the learning_ids, new title, and synthesized content 5. Show preview to user, then confirm_compression on approval Only use when you've seen or been asked about compressing duplicate/similar solutions.

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• generate_xpp_template

  ALM X++ MCP Server

  WHEN: writing an extension or customization -- generates ready-to-use X++ code. Triggers: 'génère un CoC', 'crée une extension', 'generate extension', 'write a CoC class', 'event handler pour', 'template pour'. Uses REAL metadata from the KB (actual field names, method signatures). 'coc' = Chain of Command class, 'table_extension' = extend table with fields/methods, 'event_handler' = pre/post event handler, 'job' = runnable class, 'find_method' = find/exist pattern. ALWAYS call get_object_details first to verify the object exists.

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• scan_skill

  SecurityScan

  Scan a GitHub repository or skill URL for security vulnerabilities. This tool performs static analysis and AI-powered detection to identify: - Hardcoded credentials and API keys - Remote code execution patterns - Data exfiltration attempts - Privilege escalation risks - OWASP LLM Top 10 vulnerabilities Requires a valid X-API-Key header. Cached results (24h) do not consume credits. Args: skill_url: GitHub repository URL (e.g., https://github.com/owner/repo) or raw file URL to scan Returns: ScanResult with security score (0-100), recommendation, and detected issues. Score >= 80 is SAFE, 50-79 is CAUTION, < 50 is DANGEROUS. Example: scan_skill("https://github.com/anthropics/anthropic-sdk-python")

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• code_get_file

  searchcode

  Get code from a remote public git repository — either a specific function/class by name, a line range, or a full file. PREFERRED WORKFLOW: When search results or findings have already identified a specific function, method, or class, use symbol_name to extract just that declaration. This avoids fetching entire files and keeps context focused. Only fetch full files when you need a broad understanding of a file you haven't seen before. For supported languages (Go, Python, TypeScript, JavaScript, Java, C, C++, C#, Kotlin, Swift, Rust) the response includes a symbols list of declarations with line ranges. This is not a first-call tool — use code_analyze or code_search first to identify targets, then extract precisely what you need.

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• fda_device_class

  FDA Data MCP

  Lookup FDA device classification details by product code. Returns device name, device class (I/II/III), medical specialty, regulation number, review panel, submission type, and definition. Requires: product code (3-letter code from 510(k), PMA, or device product listings). Related: fda_product_code_lookup (cross-reference across 510(k) and PMA), fda_search_510k (clearances for this product code), fda_search_pma (PMA approvals for this product code).

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• lookup_authoring_skill

  kernelcad

  Return the kernelcad-authoring SKILL.md body — conventions for writing .kcad.ts scripts (imports, parameters, evaluation contract, common pitfalls). Use this tool BEFORE generating CAD code if your MCP client does not list resources. Clients that do list resources should instead read `kernelcad://skills/authoring` directly — the contents are identical. INPUT: none. OUTPUT: { uri, mimeType, text } where `text` is the SKILL.md body.

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• get_free_resources

  Makuri Showcase (CogniLedger)

  Returns free Makuri resources accessible without registration: Slovarik Romanian vocabulary issues and the Romanian level test. Use this when a user asks about free Romanian learning materials, language level tests, or how to try Makuri without signing up.

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• generate_scaffold

  Senzing

  Generate SDK scaffold code for common workflows. Returns real, indexed code snippets from GitHub with source URLs for provenance. Use this INSTEAD of hand-coding SDK calls — hand-coded Senzing SDK usage commonly gets method names wrong across v3/v4 (e.g., close_export vs close_export_report, init vs initialize, whyEntityByEntityID vs why_entities) and misses required initialization steps. Languages: python, java, csharp, rust. Workflows: initialize, configure, add_records, delete, query, redo, stewardship, information, full_pipeline (aliases accepted: init, config, ingest, remove, search, redoer, force_resolve, info, e2e). V3 supports Python and Java only. Returns GitHub raw URLs — fetch each snippet to read the source code.

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• rating_score_writing

  website-search

  Get Lenny Zeltser's scoring playbook so your AI can score a draft locally against a cybersecurity-writing rating sheet. THIS IS THE ONLY TOOL THAT PRODUCES NUMERIC SCORES — the writing-coach tools (`get_security_writing_guidelines`, `ir_*`, `product_*`) never score. Returns the rubric plus step-by-step instructions for applying it. This server never requests your draft and instructs your AI to keep it local—rating sheets and scoring instructions flow to your AI.

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• generate_wallet

  Solentic

  Returns runnable code that creates a Solana keypair. Solentic cannot generate the keypair for you and never sees the private key — generation must happen wherever you run code (the agent process, a code-interpreter tool, a Python/Node sandbox, the user's shell). The response includes the snippet ready to execute. After running it, fund the resulting publicKey and call the `stake` tool with {walletAddress, secretKey, amountSol} to stake in one call.

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• lookup_native

  redm-mcp

  Resolve a RedM/RDR3 SCRIPT native by hash or name — O(1), exact. Use whenever you see `Citizen.InvokeNative(0x...)`, `Citizen.invokeNative('0x...')`, `GetHashKey('NAME')`, or a SCREAMING_SNAKE_CASE native name (e.g. `SET_ENTITY_COORDS`, `GetPedHealth`) in Lua/JS/TS. NOT for game-data hashes (weapon/ped/animation names) — use `grep_docs`. Pass `hash` (0x… optional, case-insensitive) or `name` (exact first, ILIKE substring fallback). Returns name, hash, namespace, return type, params, description, full content, plus `findings[]` — community gotchas linked to that native. Inspect `findings[].id` and call `get_document({path: 'learning:<id>'})` for full body.

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• generate_wallet

  Blueprint Agentic Staking (Solentic)

  Returns runnable code that creates a Solana keypair. Solentic cannot generate the keypair for you and never sees the private key — generation must happen wherever you run code (the agent process, a code-interpreter tool, a Python/Node sandbox, the user's shell). The response includes the snippet ready to execute. After running it, fund the resulting publicKey and call the `stake` tool with {walletAddress, secretKey, amountSol} to stake in one call.

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