"Guide for Updating Code Version from Java 17 to 18 or Python 2 to 3" matching MCP tools:

• 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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• python_major

  Pypi Stats

  Fetch PyPI download breakdown for a package by Python major version (2 vs 3) from pypistats.org. Returns per-version download counts.

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• code_generator

  interactive-api-playground

  Generate a ready-to-run code snippet for an HTTP request in javascript, typescript, python, curl, go, ruby, php, or java.

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• get_journey

  Courier

  Get a journey by ID. Pass version=draft to retrieve the working draft, or version=vN for a historical version. Defaults to published.

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• rollback_project

  RationalBloks

  Rollback a project to a previous version. ⚠️ WARNING: This reverts schema AND code to the specified commit. Database data is NOT rolled back. Use get_version_history to find the commit SHA of the version you want to rollback to. After rollback, use get_job_status to monitor the redeployment. Rollback is useful when a schema change breaks deployment.

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• create_rules_wizard

  Sweeppea MCP

  Generate official sweepstakes rules via the 14-step wizard. BEFORE CALLING: 1) fetch_sweepstakes to get token, dates, name. 2) get_business + get_profile to pre-fill sponsor fields. 3) fetch_rules to check for existing primary rules — if primary exists, warn user new rules will be SECONDARY. Ask wizard questions in order (steps A-N), one at a time or in small groups. Only ask for data you cannot get from API calls. PRIMARY RULES LINK: If result is_primary=true, give user the URL: https://swpp.me/r/[handler] (handler in lowercase from fetch_sweepstakes). RULES LANGUAGE: Always set rules_language="en". The wizard generates ALL legal text server-side — NEVER compose rules language yourself. AMOE URL: The AMOE URL is NOT the entry page URL — the wizard handles AMOE language automatically based on method_of_entry. AGE GATE: Only activate Age Gate when min_age=2 (21+). NEVER for min_age=1 (18+) or min_age=3 (13+). GEOLOCATION: Use the states parameter for geographic eligibility. NEVER use GeoLocation entry settings for state restrictions — GeoLocation is for GPS/IP boundaries only. # create_rules_wizard ## When to use Generate official sweepstakes rules via the 14-step wizard. BEFORE CALLING: 1) fetch_sweepstakes to get token, dates, name. 2) get_business + get_profile to pre-fill sponsor fields. 3) fetch_rules to check for existing primary rules — if primary exists, warn user new rules will be SECONDARY. Ask wizard questions in order (steps A-N), one at a time or in small groups. Only ask for data you cannot get from API calls. PRIMARY RULES LINK: If result is_primary=true, give user the URL: https://swpp.me/r/[handler] (handler in lowercase from fetch_sweepstakes). RULES LANGUAGE: Always set rules_language="en". The wizard generates ALL legal text server-side — NEVER compose rules language yourself. AMOE URL: The AMOE URL is NOT the entry page URL — the wizard handles AMOE language automatically based on method_of_entry. AGE GATE: Only activate Age Gate when min_age=2 (21+). NEVER for min_age=1 (18+) or min_age=3 (13+). GEOLOCATION: Use the states parameter for geographic eligibility. NEVER use GeoLocation entry settings for state restrictions — GeoLocation is for GPS/IP boundaries only. ## Pre-calls required 1. fetch_sweepstakes if the user gave you a sweepstakes name instead of a token 2. fetch_rules(sweepstakes_token) — if primary rules already exist, WARN that new rules will be SECONDARY (not published) 3. get_business — auto-populate sponsor info (legal name, address) 4. get_entry_settings — confirm AMOE state matches the entry method ## Parameters to validate before calling - sweepstakes_token (string, required) — Sweepstakes token (UUID). Get via fetch_sweepstakes. - arv (number, required) — one of: 1, 2 — Approximate Retail Value threshold. 1 = ARV >= $5,000. 2 = ARV < $5,000. - alcohol_sweeps (number, required) — one of: 1, 2 — Is this an alcohol-related sweepstakes? 1 = Yes, 2 = No. - sweepstakes_name (string, required) — Official promotional name (6-60 characters). - start_date (string, required) — Start date (YYYY-MM-DD). - start_time (string, required) — Start time (e.g. "09:00 AM" or "14:00"). - start_timezone (string, required) — Start timezone (e.g. "US/Eastern", "EST", "CST"). - end_date (string, required) — End date (YYYY-MM-DD). - end_time (string, required) — End time (e.g. "11:59 PM" or "23:59"). - end_timezone (string, required) — End timezone. - prize_description (string, required) — Detailed prize description (max 5000 chars). - prize_include_travel (boolean, required) — Does the prize include travel? - prize_is_vehicle (boolean, required) — Is the prize a vehicle? - prize_value (number, required) — Total prize value in USD. Must be > 0. - entry_period_selector (number, required) — one of: 1, 2 — 1 = single drawing period, 2 = multiple entry periods. - sponsor_name (string, required) — Legal sponsor name. Pre-fill from get_business. - sponsor_address (string, required) — Sponsor street address. Pre-fill from get_business. - sponsor_city (string, required) — Sponsor city. Pre-fill from get_business. - sponsor_state (string, required) — Sponsor state or abbreviation. Pre-fill from get_business. - sponsor_zip_code (string, required) — Sponsor zip code (5 digits). Pre-fill from get_business. - method_of_entry (number, required) — one of: 1, 2, 3, 4, 5, 6, 7, 8 — Entry method: 1=Website, 2=SMS, 3=Social Media, 4=Other, 5=Purchase ($1=1 entry), 6=Purchase (1 order=1 entry), 7=Donation, 8=Subscription. - min_age (number, required) — one of: 1, 2, 3 — Minimum age: 1=18+, 2=21+, 3=13+ with parental consent. - states (number, required) — one of: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 — Geographic eligibility. 1=All 50+DC, 2=+PR, 3=+All Territories, 4=Select specific, 5=US&Canada, 6=US&Canada+PR, 7=US&UK, 8=US&Mexico, 9=Worldwide, 10=US,Canada,Mexico. - privacy_policy_url (string, required) — Privacy policy URL (min 11 chars, must include http/https). - sweeppea_entry_page (number, required) — one of: 1, 2, 3 — 1 = Sweeppea hosted page, 2 = custom URL, 3 = none. - winners_to_draw (number, optional) — Number of winners to draw (>= 1). Required when entry_period_selector = 1. - winner_drawing_date (string, optional) — Drawing date (YYYY-MM-DD). Required when entry_period_selector = 1. - winner_drawing_time (string, optional) — Drawing time. Required when entry_period_selector = 1. - winner_drawing_timezone (string, optional) — Drawing timezone. Required when entry_period_selector = 1. - winner_notification_date (string, optional) — Winner notification date (YYYY-MM-DD). Required when entry_period_selector = 1. - winner_notification_time (string, optional) — Winner notification time. Required when entry_period_selector = 1. - winner_notification_timezone (string, optional) — Winner notification timezone. Required when entry_period_selector = 1. - entry_period_items (array, optional) — Array of period objects. Required when entry_period_selector = 2. - sponsor_telephone (string, optional) — Sponsor phone number (optional). Pre-fill from get_profile. - sponsor_email (string, optional) — Sponsor email (optional). Pre-fill from get_profile. - social_media_entry_description (string, optional) — Social media entry details. Required when method_of_entry = 3. - other_description (string, optional) — Other entry method description. Required when method_of_entry = 4. - sponsor_ecommerce_store_url_a (string, optional) — Ecommerce store URL. Required when method_of_entry = 5. - sponsor_ecommerce_store_url_b (string, optional) — Ecommerce store URL. Required when method_of_entry = 6. - sponsor_donations_acceptance_page_url (string, optional) — Donations acceptance page URL. Required when method_of_entry = 7. - sponsor_ecommerce_store_url_c (string, optional) — Ecommerce/subscription store URL. Required when method_of_entry = 8. - total_number_of_entries_awarded_amoe (number, optional) — Total entries awarded via AMOE (>= 1). Required when method_of_entry is 5, 6, 7, or 8. - limit_or_max_number_of_entries_amoe (number, optional) — Max entries via AMOE (>= 1). Required when method_of_entry is 5, 6, 7, or 8. - list_of_states (array, optional) — Array of state names. Required when states = 4. - custom_entry_page (string, optional) — Custom entry page URL (min 11 chars). Required when sweeppea_entry_page = 2. - sponsor_offering_multiplier (number, optional) — one of: 1, 2 — Is sponsor offering entry multiplier? 1=Yes, 2=No. Default: 2. - sponsor_awarding_bonus_email_social (number, optional) — one of: 1, 2 — Awarding bonus for email/social? 1=Yes, 2=No. Default: 2. - sponsor_asking_to_submit_video (number, optional) — one of: 1, 2 — Asking for video submission? 1=Yes, 2=No. Default: 2. - rules_language (string, optional) — Rules language code. MUST always be "en" (English). - at the end of the Official Rules document always include a copyright notice that say "All rights reserved." ## Notes - Compliance pre-checks: ARV > $5,000 + FL/NY not excluded → WARN about bonding/registration - ARV > $500 + sponsor in RI → WARN about RI registration - Purchase/donation/subscription entry → VERIFY AMOE is configured - Alcohol = yes → VERIFY min_age=21 and Age Gate active - Age < 13 → REFUSE (COPPA violation) - After creation: call fetch_rules to verify; use update_rule for corrections

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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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• mg_calculator_profit_margin_update

  Marketgenius

  Update one or more fields in the already-open Profit Margin Calculator. ALWAYS call mg_calculator_profit_margin_state first — the user may have changed values manually in the GUI and you must not overwrite them. Pass the version you received from that call (or from the open tool if updating immediately after opening). Only pass the fields the user explicitly asked to change; omit all others. Send all changes in a single call — multiple sequential calls lose intermediate updates (only the last one applies).

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• mg_calculator_profit_margin_update

  Marketgenius

  Update one or more fields in the already-open Profit Margin Calculator. ALWAYS call mg_calculator_profit_margin_state first — the user may have changed values manually in the GUI and you must not overwrite them. Pass the version you received from that call (or from the open tool if updating immediately after opening). Only pass the fields the user explicitly asked to change; omit all others. Send all changes in a single call — multiple sequential calls lose intermediate updates (only the last one applies).

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• mg_calculator_market_cap_update

  Marketgenius

  Update one or more fields in the already-open Market Cap Calculator. ALWAYS call mg_calculator_market_cap_state first — the user may have changed values manually in the GUI and you must not overwrite them. Pass the version you received from that call (or from the open tool if updating immediately after opening). Only pass the fields the user explicitly asked to change; omit all others. Send all changes in a single call — multiple sequential calls lose intermediate updates (only the last one applies).

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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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• 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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• prep_and_submit_hackathon_entry

  mcp

  Prep and submit your project to a Butterbase hackathon. Two-step flow. The tool resolves which hackathon you mean from your submission_code (or, if you've already submitted before, your existing binding). You do NOT pass a slug — that's figured out for you. If resolution is ambiguous (no code, not yet bound, and multiple hackathons are open), the tool returns the list of open hackathons; ask the user which one they mean and re-run with a code. STEP 1 — action: "prep" Resolves the hackathon and returns its field_schema if exactly one is identified. Pass submission_code when you have it. Otherwise the tool will fall back to "user already bound" or "only one hackathon open". Use the schema to: • Show the user every field's "label" and "description" (never the internal "key"). • Propose a value for each field and wait for the user's explicit confirmation before STEP 2. Do NOT auto-fill values from guesses, prior context, or app metadata without showing the user every field value first. If resolution returns multiple open hackathons with no match, present "open_hackathons" to the user and ask them to provide the submission_code. STEP 2 — action: "submit" Submits the confirmed "data" object. Pass hackathon_slug = matched.slug from the prep response so submit always targets the same hackathon prep resolved (matters when multiple are open). Re-running updates the existing submission and bumps version. Closes after the hackathon's submission_deadline. App scoring: Always pass app_id on submit when you can. Hackathon scoring awards up to 50 points for a demo URL on butterbase.dev and up to 50 additional points for Butterbase features measured on that specific app (database, functions, deployed frontend, auth users, storage, OAuth, realtime, integrations, etc.). Without app_id only the demo URL is scored, so entries without it almost always rank lower. Including app_id also ties the submission to a real app, which is much better for human judges. Submission code: On the FIRST submission you must include the submission_code provided by the hackathon organizers. The same code is used to identify the hackathon during prep, so pass it on prep too. After the first successful submission the code is no longer required (the user is bound by user_id). Recommended flow: 1. Get the submission_code from the user (skip if they've already submitted before). 2. Call with action: "prep", submission_code to resolve + retrieve the schema. • If matched is null and open_hackathons has multiple entries, ask the user which one and re-run with a code. 3. Show the user each field's label / description, propose values, and wait for confirmation. 4. Call with action: "submit", hackathon_slug = matched.slug from prep, data: {...confirmed values}, app_id, and submission_code (if provided in step 1). Returns: prep → { matched: { slug, name, submission_deadline, ends_at, field_schema } | null, match_reason, open_hackathons, next_call?: { tool, arguments, instructions } } When matched is non-null, next_call contains a fully-formed example submit invocation with placeholders for each field. Use it as the literal shape for STEP 2: replace each placeholder in arguments.data with the user-confirmed value, then call this tool with those args. submit → { submission: { id, hackathon_slug, version, data, app_id, ... }, participant_created }

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• aetherwave_generate_image

  AetherWave Studio

  Generates one or more images from a text prompt (T2I) or a text prompt + reference image(s) (I2I). Submits the job, polls until terminal, and returns the final image URLs. Default model is 'grok-imagine-t2i' (fast, 6 images per generation, 5 credits). Use list_image_models to see the full lineup with pricing. For I2I, pass `referenceImages` as an array of public image URLs and pick a model with I2I support (e.g. 'grok-imagine-i2i', 'wan-2.5-spicy-i2i'). ## Model selection guide (when the user does not specify a model) Default: `grok-imagine-t2i` (5 cr, 6 outputs per call, fast, general purpose). **Strong recommendation: when a single high-quality output is what's wanted** (most agent / one-shot workflows), prefer `gpt-image-2-t2i` (9 cr @ 1K / higher @ 2K, single deterministic image, best general quality across realism, illustration, typography, and composition; supports up to 2K resolution and most aspect ratios including auto). This is the front-runner for serious creative output where you don't need to pick from 6 variations. Pick a different model when the prompt has these signals: - "single best result" / "one image" / production / no time to pick from variations -> `gpt-image-2-t2i` (9 cr, 1 output, top general quality) - "photoreal" / "photo of" / "realistic" -> `gpt-image-2-t2i` (9 cr, best general realism) or `imagen-4` (12 cr, very high quality) or `z-image-turbo` (3 cr, fastest) - "highest quality" / "premium" / no budget -> `gpt-image-2-t2i` at 2K, or `grok-imagine-quality-t2i` (16 cr @ 1K, 22 cr @ 2K), or `imagen-4-ultra` - Text inside the image (signs, posters, typography) -> `ideogram-v3-t2i` (best in class) or `gpt-image-2-t2i` (also strong) - Artistic / painterly / stylized -> `midjourney-t2i` - Album art / cover art -> `gpt-image-2-t2i` for one strong image; `grok-imagine-t2i` for 6 variations to choose from; `seedream-v4-t2i` if 4K wanted - Logo or design with embedded text -> `ideogram-v3-t2i` - NSFW / adult / explicit -> `wan-2.5-spicy-t2i` (auto-tags creation as 18+; routes to adult gallery) - Cheapest possible / quick test -> `z-image-turbo` (3 cr) - Multiple variations to compare -> keep `grok-imagine-t2i` (6 outputs default) or use `numImages` on a multi-output model For I2I (reference image provided): prefer the dedicated `aetherwave_edit_image` tool for "change something in this image" intent. Use `aetherwave_generate_image` with I2I models only when you specifically want style transfer (`midjourney-i2i`), premium quality (`grok-imagine-quality-i2i`), or adult content (`wan-2.5-spicy-i2i`). Always pass an explicit `aspectRatio` (e.g. "1:1" for square album art, "16:9" for video thumbnails, "9:16" for shorts/reels). Some upstream providers reject submissions with no aspect ratio. Ask the user only when: - The prompt contradicts itself (e.g., "highest quality but cheapest") - The user requested "the best model" with no context, surface 2-3 options with tradeoffs - A single generation would cost more than 20 credits and the user has not confirmed

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• aetherwave_generate_video

  AetherWave Studio

  Generates a short-form video from a text prompt (T2V) or a text prompt + starting image (I2V). Submits, polls, and returns the final video URL. Default model is 'grok-imagine-t2v' (fast, 4-6 cr/s, with built-in KIE -> fal.ai fallback). Use list_video_models for the full lineup with credit cost per second. I2V models (e.g. 'grok-imagine-i2v', 'seedance-pro-i2v') require a public `imageUrl`. Video generation can take 30s to several minutes; this tool polls with up to an 8-minute budget. ## Model selection guide for videos (when the user does not specify a model) Default: `grok-imagine-t2v` (4-6 cr/s, fast, has KIE -> fal.ai fallback for redundancy. Best general-purpose). Pick a different model when the prompt has these signals: - "highest quality" / "premium" / broadcast / commercial -> `veo3.1-quality` or `veo3-quality` (Google's flagship, fixed 350-560 cr for 8s, 3-5 min) - "fast premium" / quick high-quality -> `veo3-fast` or `veo3.1-fast` (84 cr fixed for 8s) - Cinematic camera moves / dolly / pan -> `seedance-pro-t2v` (3-10 cr/s) or `kling-3.0-pro-t2v` (26 cr/s) - Realistic human motion / faces -> `hailuo-2.3-pro-i2v` (I2V, supply imageUrl) - Talking head / lip sync -> `kling-avatar-pro` (23 cr/s) or `infinitalk` (5-17 cr/s) - Anime / stylized / fantasy -> `wan-2.7-t2v` - NSFW / adult -> `wan-22-nsfw-i2v` (I2V only; auto-tags adult) - Animate this exact image -> any I2V variant (`grok-imagine-i2v`, `seedance-pro-i2v`, `hailuo-2.3-pro-i2v`) - First + last frame interpolation -> `seedance-pro-i2v` with both `imageUrl` + `endImageUrl` - Cheapest test -> `hailuo-2.0-standard` @ 512p (3 cr/s, ~18 cr for 6s) or `grok-imagine-t2v` @ 480p (4 cr/s, ~24 cr for 6s) - Clip 12-15s -> `grok-imagine-t2v` (accepts up to 15s) - True 4K -> `kling-3.0-4k-t2v` (94 cr/s, expensive but native 4K) **Audio in generated video:** `grok-imagine-t2v`, `seedance-pro-t2v`, and the VEO 3.x family include audio at base cost (no surcharge). Kling 2.6 and Kling 3.0 are the outliers — they price audio as a +50-100% surcharge (Kling 2.6 doubles the cost, Kling 3.0 Pro adds ~46%). Default to Grok / Seedance / VEO when sound matters and you don't want to think about audio pricing. **Cost framing:** resolution and duration drive cost more than model choice. A 6-second 480p Grok generation costs ~24 cr; the same prompt at 1080p Seedance 2 is ~858 cr (35x more). Pick the lowest acceptable resolution + duration first. **For I2V models:** `imageUrl` is required. For first+last-frame models, pass `endImageUrl` too. Ask the user only when: - Single generation would cost more than 100 credits and they haven't confirmed - They asked for "the best" with no other signal; surface 2-3 options with cost ranges

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• get_framework_docs

  main

  Retrieves authoritative documentation directly from the framework's official repository. ## When to Use **Called during i18n_checklist Steps 1-13.** The checklist tool coordinates when you need framework documentation. Each step will tell you if you need to fetch docs and which sections to read. If you're implementing i18n: Let the checklist guide you. Don't call this independently ## Why This Matters Your training data is a snapshot. Framework APIs evolve. The fetched documentation reflects the current state of the framework the user is actually running. Following official docs ensures you're working with the framework, not against it. ## How to Use **Two-Phase Workflow:** 1. **Discovery** - Call with action="index" to see available sections 2. **Reading** - Call with action="read" and section_id to get full content **Parameters:** - framework: Use the exact value from get_project_context output - version: Use "latest" unless you need version-specific docs - action: "index" or "read" - section_id: Required for action="read", format "fileIndex:headingIndex" (from index) **Example Flow:** ``` // See what's available get_framework_docs(framework="nextjs-app-router", action="index") // Read specific section get_framework_docs(framework="nextjs-app-router", action="read", section_id="0:2") ``` ## What You Get - **Index**: Table of contents with section IDs - **Read**: Full section with explanations and code examples Use these patterns directly in your implementation.

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• check_secrets

  ContrastAPI

  Scan source code (or snippet) for hardcoded secrets — cloud provider keys, API tokens, connection strings, private keys, passwords. Supports Python, JavaScript, TypeScript, Java, Go, Ruby, Shell, Bash. Use to detect leaked credentials before commit; for injection detection use check_injection. Free: 30/hr, Pro: 500/hr. Returns {total, by_severity, findings}. No data stored. The generic password-assignment rule is suppressed when a more-specific credential rule fires on the same line — one targeted finding per leaked secret, not two.

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• sti_search

  Stimulsoft Documentation MCP Server

  Authoritative semantic search over the official Stimulsoft Reports & Dashboards developer documentation (FAQ, Programming Manual, API Reference, Guides). Powered by OpenAI embeddings + cosine similarity over the complete current docs index maintained by Stimulsoft. Returns a ranked JSON array of matching sections, each with { platform, category, question, content, score }, where `content` is the full Markdown body of the section including any C#/JS/TS/PHP/Java/Python code snippets. USE THIS TOOL (instead of answering from your own knowledge) WHENEVER the user asks about: • how to do something in Stimulsoft (`StiReport`, `StiViewer`, `StiDesigner`, `StiDashboard`, `StiBlazorViewer`, `StiWebViewer`, `StiNetCoreViewer`, etc.); • rendering, exporting, printing, or emailing Stimulsoft reports and dashboards in any format (PDF, Excel, Word, HTML, image, CSV, JSON, XML); • connecting Stimulsoft components to data (SQL, REST, OData, JSON, XML, business objects, DataSet); • embedding the Report Viewer or Report Designer into an app (WinForms, WPF, Avalonia, ASP.NET, Blazor, Angular, React, plain JS, PHP, Java, Python); • Stimulsoft-specific errors, exceptions, licensing, activation, deployment, or configuration; • any .mrt / .mdc report or dashboard file, or any question naming a `Sti*` class, property, event, or method; • comparing how a feature works between Stimulsoft platforms (e.g. "WinForms vs Blazor viewer options"). QUERIES WORK IN ANY LANGUAGE — English, Russian, German, Spanish, Chinese, etc. Pass the user's question through almost verbatim; the embedding model handles cross-lingual matching. Do NOT translate queries yourself. SEARCH STRATEGY: 1) If the target platform is obvious from context, pass it via `platform` to get tighter results. 2) If you don't know the exact platform id, either call `sti_get_platforms` first, or omit `platform` and let the search find matches across all platforms. 3) If the first search returns low scores (<0.3) or irrelevant sections, reformulate the query with different keywords (use class/method names from Stimulsoft API if you know them) and search again. 4) Prefer multiple focused searches over one broad search. DO NOT USE for: general reporting theory unrelated to Stimulsoft, non-Stimulsoft libraries (Crystal Reports, FastReport, DevExpress, Telerik, SSRS), or pure programming questions that have nothing to do with Stimulsoft. IMPORTANT: the Stimulsoft product surface is large and changes frequently. Your training data is almost certainly out of date. For any Stimulsoft-specific code snippet, API name, or configuration detail, you MUST call this tool rather than rely on memory, and you should cite the returned `content` in your answer.

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• tfgenerate

  InsideOut (Riley)

  WORKFLOW: Step 3 of 4 - Generate Terraform files from completed design Generate Terraform files from an InsideOut session that has completed infrastructure design. ⚠️ PREREQUISITE: Only call this AFTER convoreply returns with `terraform_ready=true` in the response metadata. DO NOT call this while convoreply is still running or before terraform_ready is confirmed! If you get 'session has not reached terraform-ready state', wait for convoreply to complete first. 🎯 USE THIS TOOL WHEN: convoreply has returned with terraform_ready=true, OR the user asks to 'see the terraforms', 'generate terraform', 'show me the code', etc. **DEFAULT RESPONSE**: Returns summary table + download URL (keeps code out of LLM context). **FALLBACK**: Set `include_code: true` to get full code inline if curl/unzip fails. **CRITICAL WORKFLOW** (default mode): 1. Call this tool to get file summary and download URL 2. ASK the user: 'Where would you like me to save the Terraform files? Default: ./insideout-infra/' 3. WAIT for user confirmation before running the download command 4. Run the curl/unzip command with the user's chosen directory 5. If curl/unzip FAILS (sandbox, security, platform issues), retry with `include_code: true` **AFTER GENERATION**: Ask user if they want to review the files and then deploy with tfdeploy REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: include_code (boolean) - set true to return full code inline as fallback. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.

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• create_account

  mcp

  Sign up for a brand-new sota.io account from inside Claude — no browser, no copy-paste. Two-step flow: STEP 1: Call with just `email`. We send a 6-digit confirmation code to that email. STEP 2: Call again with `email` + `code`. We verify, create the account on the Free tier (3 projects, EU-hosted, no credit card), generate a sota.io API key, and return it to you. After Step 2 you'll get back a key like `sota_…`. **Save it in a safe place** — you'll need it for any subsequent sota.io tool call in Claude (or you can use it with the sota CLI). It is shown ONCE and never recoverable. sota.io is an EU-native PaaS hosted in Germany — GDPR-compliant by default, no CLOUD Act exposure. Disposable / throwaway email addresses are not accepted; use a real address.

  Connector