"Coding in Python and R" matching MCP tools:

• map_icd10_to_icd11

  Medical Terminologies MCP

  Authoritative ICD-10 → ICD-11 mapping using WHO transition tables (release 2025-01, bundled with the server). Returns the primary 1:1 ICD-11 category for the ICD-10 code plus any alternative ICD-11 candidates that WHO documents (some ICD-10 concepts split into multiple ICD-11 entities). For each mapping, includes the ICD-11 code, title, chapter, and the Foundation URI / Linearization URI for navigating to the full entity definition. Use this for clinical coding, billing migration, retrospective analysis, and any workflow that needs authoritative mapping rather than text-search candidates. Coverage: 11,243 ICD-10 categories (excludes chapters and blocks like "A00-A09" which aren't used in clinical coding). Provide a code like "E11" (Type 2 diabetes), "I21" (Acute MI), or "A07.8" (4 alternatives in WHO's table). Both dotted ("A07.8") and undotted ("A078") forms are accepted. Returns "no mapping" when the code isn't in the WHO category-level table — that's the honest answer rather than a fuzzy search fallback.

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• get_chain_controls

  commutescout

  Current chain-control requirements on California mountain highways. Data: Caltrans chain-control status for fixed checkpoints on mountain routes (I-80 Donner, US-50 Echo Summit, SR-88, SR-89, and others). Levels: R-1 = chains OR snow tires required; R-2 = chains required except 4WD/AWD with snow tires on all four; R-3 = chains on ALL vehicles (rare, usually precedes closure). Refresh: 5-minute cache. Filters: route (e.g. "80", "US-50", "SR-88"); center "lat,lon" with radius_km for all checkpoints around a place (e.g. around Truckee), whatever highway they are on. Off-season (roughly May-October) there are usually no controls anywhere; the response says so explicitly rather than returning an empty list. Chain requirements can change hour to hour in storms - tell the user the data_as_of time and to carry chains anyway when snow is possible.

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• validate_python

  Python Code Validator

  Check Python source without running it: parse, lint (ruff), type-check (mypy), AST security policy, credential scan. Safe on code you do not trust. Use it on every Python file you generated or edited, before writing it to disk. Alternatives: repair_python to get the corrected source instead of the diagnosis; execute_python to prove the code runs. Auth: a key is required. A free key covers this call, 25 per day, then HTTP 429; get one with POST /v1/keys. Credits are bought without an account, 1 per call: GET /v1/pricing says where to send the xDAI. Arguments: code: the whole file, 1..200000 bytes of UTF-8 measured after encoding (empty is refused with 400, larger with 413); a fragment is fine, but line and column numbers in the answer count from 1 in what you sent. language: must be 'python'; anything else is 400, and the field may be omitted. Of options only transpile_to (e.g. 'javascript', which returns a translated copy in transpiled) acts here; timeout_s, max_iterations, optimize, examples and expected_output need a pass that rewrites or runs the code, so send code alone. Ignored options are not refused, so a call that sets them looks like it worked; and code that does not parse is answered rather than refused: valid=false with the syntax error located, which is the point. Returns valid, score 0..1, diagnostics (rule, message, line, column), security findings, fixes, fixed_code and runtime; see outputSchema. The code and its verdict are retained to improve the service.

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• list_services

  Escola de Rádio TV & Web (ER+)

  Lista serviços oferecidos pela ER+ ALÉM dos cursos regulares: 'demo' (gravação de demo profissional com Ruy, R$ 350), 'mentoria' (mentoria 1:1 com Ruy, R$ 250/h), 'b2b' (treinamentos corporativos pra empresas). Use quando aluno perguntar sobre demo, mentoria, treinamento empresarial. Pra cursos regulares, use list_courses.

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• amend_trade

  mcp

  [JOURNAL] Amend an OPEN journal trade by trade_id: move your stop or target, fix size_usd / leverage / thesis. A stop MOVE changes only the current stop (what the watchdog and close-time touch scan use); realized R stays measured against your INITIAL stop, so trailing to breakeven can't inflate R. To fix a genuine fat-finger in the original entry or stop, also pass correct_entry=true — that resets the R basis (disclosed in the response). asset/side can't be amended — void and re-log for that. Pro.

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• render_diagram

  Diagrams MCP

  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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• get_integration_guide

  TestMyVibes

  Returns the canonical guide for using TMV from a coding-agent context. Covers the fix-test-retest loop, how to write a good test prompt, how to read the actionTrail / consoleErrors / failedRequests outputs, and common gotchas. Call this first if you're a new agent on a project — it'll save you a debug session. The same content is served at https://testmyvibes.com/docs/coding-agents.

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• get_capital_allocation_profile

  Valuein — SEC EDGAR Fundamentals & Smart-Money Data

  Get a multi-year capital allocation breakdown for a US public company. Shows how management deploys cash across all six categories — capex, R&D, M&A, dividends, buybacks, and debt — plus pre-computed deployment ratios (% of operating cash flow) and over-distribution flags. Use this tool when the user asks: how does a company allocate capital, what's the buyback-vs-dividend mix, is the company over-distributing, is growth funded by R&D or M&A, what's the cash-return-ratio trend, or any 'where does the money go' question — including owner-earnings (Buffett-style) and reinvestment-rate (Damodaran-style) analysis. Data sourced from annual 10-K filings; PIT-safe via as_of_date. R&D is included as a deployment category (the primary growth-reinvestment vehicle for knowledge-economy firms), but since it's already deducted before operating cash flow, `rd_pct_ocf` is INFORMATIONAL and `total_deployment_pct_ocf` EXCLUDES R&D to preserve the cash-flow identity (OCF = capex + M&A + dividends + buybacks + debt repayment + Δcash). The `flags` object carries pre-computed booleans: `buybacks_exceed_fcf`, `total_returns_exceed_fcf` (buybacks + dividends > FCF), and `debt_funded_distribution` (over-distribution funded by leverage vs cash). Available on all plans.

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• lora_airtime

  calc.engineer

  Calculates LoRa packet time-on-air using the Semtech AN1200.13 formula. Computes symbol duration, preamble time, payload symbol count, effective data rate, and the minimum transmission interval for 1% duty cycle compliance. Essential for capacity planning in LoRaWAN and Meshtastic mesh networks. Accepts spreading factor (SF7-SF12), bandwidth (125/250/500 kHz), coding rate (4/5-4/8), payload size, header mode, CRC, and optional low data rate optimization. Feeds airtime_ms to channel_utilization for mesh load analysis.

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• get_track_record

  mcp

  Get the realised track record: win-rate + R-multiple distribution. Aggregates actual closed outcomes (tp_hit, trail_stop_hit, stop_hit, position_closed) into an honest scorecard — win_rate, wins/losses, and the realised-R distribution (mean/median/min/max/total). Pass a ticker for its per-ticker record; omit it (or pass "") for the portfolio-wide record. HONESTY: small samples are flagged `illustrative: true` with an explanatory `note`, and `win_rate` is null when no closed P&L exists. Never present an illustrative record as a reliable hit-rate. Every number is grounded in stored outcome events — none are fabricated. This is the ground-truth check on signal quality: a high stated R:R only holds if the realised-R mean is positive and the stop-hit rate is low. Args: ticker: Stock ticker (e.g. "AAPL"), or "" for portfolio-wide. Returns a dict with scope, sample_size, win_rate, realised_r, and note.

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• device_tap

  Robot Actions — Remote Device Control

  Tap at (x,y) coordinates on a device screen. Coordinates are in DEVICE TAP-COORD SPACE (the "Tap-coord space" dims printed in the device_screenshot footer; same space as device_page_source bounds). First call starts a device control session (~3s). COORDINATE SOURCES — in priority order: 1. PRIMARY: device_page_source bounds [L,T][R,B] (or the "Labeled elements" block bundled with device_screenshot) → tap center = ((L+R)/2, (T+B)/2). NO scaling. Pixel-exact. 2. FALLBACK ONLY (element not in page_source — image-only widget / custom Canvas): visual estimate from the screenshot pixels, scaled with the formula below. VISUAL → TAP COORDINATE FORMULA (Android): scale = device_width / rendered_chat_width tap_x = visual_x × scale tap_y = visual_y × scale where `device_width` is the "Tap-coord space" width from the device_screenshot footer and `rendered_chat_width` is the "Image" width from the same footer. Both axes share one scale (aspect preserved). The footer prints concrete values per device — never assume any constant. Skipping the scale on a visual estimate is the #1 cause of taps landing in the wrong place — the agent sees a downscaled image but device_tap expects full-resolution tap-space coords.

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• get_journal

  mcp

  [JOURNAL] Read your private trade journal. status=open|closed|void|all (default all shows open+closed; void is hidden unless asked), limit for history (default 20). Open trades include live unrealized PnL/R and a warning if your stop level has traded since entry. Closed trades include resolved outcomes (ret %, R, MAE/MFE). stats block = personal calibration: win rate and realized R per n0brains entry grade — where your entries were actually good. Pro.

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• search_docs

  Devdocs Io

  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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• 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).

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• search_agent_directory

  TensorFeed

  Search the TensorFeed Agent Self-Directory for hireable AI agents. Filter by skill (from a controlled vocab including research, data-analysis, coding, content-writing, voice-acting, image-generation, etc), service_area (research/data/coding/writing/voice/image/video/other), language (BCP 47), availability, hourly rate cap, minimum years of experience, or verified-hireable status. Verified-hireable members (operators paying $5 USDC/30 days for top-tier visibility) sort first. Free tier capped at 25 results. Returns wallet, display_name, operator_url, skills, rates, languages, years_experience, composite reputation rank, trust grade. TF publishes self-descriptions; TF takes no fee from off-platform transactions between operators and the agents who contact them.

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• get_subreddit

  Reddit

  Get posts from a REDDIT subreddit — r/LocalLLaMA, r/python, r/news. PREFER for "what are people posting in r/<sub>", "whats new on r/<sub> today", "top posts on Reddit this week". Sorted hot (default), new, top, rising, or controversial. For "top"/"controversial" pass a time window (day/week/month/year/all) — e.g. "top posts in r/programming this week". Returns post id, title, author, permalink, date, and a body snippet. (Vote score and comment count are not available via Reddit RSS.)

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• find_drivers

  Autario Data Analytics Platform

  KILLER ANALYSIS: given a target KPI + multiple candidate indicators, rank which candidates best predict the target by correlation strength. Perfect for "what moves my KPI?" questions. Returns ranked list with r, p-value, R² for each candidate. Maximum 30 candidates per call.

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• search-music-docs

  Music Studio

  Search detailed documentation for Strudel live coding or ABC/ABCJS notation. Returns relevant code examples and explanations from the official docs. Use this when the curated guides (get-strudel-guide, get-music-guide) don't cover what you need — for specific functions, advanced techniques, or when you're unsure about syntax. Powered by semantic search over strudel.cc and ABCJS docs.

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• get_journal

  n0brains

  [JOURNAL] Read your private trade journal. status=open|closed|void|all (default all shows open+closed; void is hidden unless asked), limit for history (default 20). Open trades include live unrealized PnL/R and a warning if your stop level has traded since entry. Closed trades include resolved outcomes (ret %, R, MAE/MFE). stats block = personal calibration: win rate and realized R per n0brains entry grade — where your entries were actually good. Pro.

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• list_loadouts

  MCPExplorer

  List curated loadouts — deliberately-assembled kits of MCP servers + governance + plays for a specific job (GTM, coding, research, support, infra). The agent-facing version of the /loadouts product. Use get_loadout for the full kit with live trust.

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