"General inquiry or casual greeting" matching MCP tools:

• asterwise_get_horoscope

  Asterwise

  Fetches an AI-synthesised Moon-sign horoscope for a chosen horizon and returns structured guidance fields plus metadata about the model and period. SECTION: WHAT THIS TOOL COVERS Calls the upstream horoscope service for a lunar sign (English or Sanskrit input accepted; response normalises moon_sign to lowercase English) and a period of daily, weekly, monthly, or yearly. It returns narrative and checklist-style content for life areas, remedy, and timing flavour text. It does not compute a personal natal chart, divisional charts, or dasha — only sign-level transit-flavoured copy tied to the requested horizon. SECTION: WORKFLOW BEFORE: None — this tool is standalone. AFTER: asterwise_get_natal_chart — if the user needs a personalised chart beyond sign-general copy. SECTION: INPUT CONTRACT period is constrained to the tool schema enum (daily, weekly, monthly, yearly). moon_sign accepts Sanskrit (Tula, Vrischika, Karka, Simha, Kanya, Dhanu, Makara, Kumbha, Meena, Mesha, Vrishabha, Mithuna) or English (Libra, Scorpio, Cancer, Leo, Virgo, Sagittarius, Capricorn, Aquarius, Pisces, Aries, Taurus, Gemini); resolution is upstream. response_format selects JSON vs markdown rendering only. SECTION: OUTPUT CONTRACT data.content: do[] (string array) body (string) love (string) avoid[] (string array) money (string) career (string) remedy (string) headline (string) narrative (string) open_loop (string) data.model_used (string — AI model version label) data.generated_at (string — ISO UTC) data.period_key (string — YYYY-MM-DD for daily; identifier for other horizons) data.horizon (string — 'daily', 'weekly', 'monthly', or 'yearly') data.moon_sign (string — lowercase English, e.g. 'libra') SECTION: RESPONSE FORMAT response_format=json serialises the complete response as indented JSON — use this for programmatic parsing, typed clients, and downstream tool chaining. response_format=markdown renders the same data as a human-readable report. Both modes return identical underlying data — no fields are added, removed, or filtered by either mode. SECTION: COMPUTE CLASS FAST_LOOKUP SECTION: ERROR CONTRACT INVALID_PARAMS (local — caught before upstream call): — Invalid period enum or other Pydantic field violations on the tool schema → MCP INVALID_PARAMS INVALID_PARAMS (upstream): — Unknown or unsupported moon_sign → MCP INTERNAL_ERROR at the tool layer (upstream rejection). INTERNAL_ERROR: — Any upstream API failure or timeout → MCP INTERNAL_ERROR Edge cases: — Sign-level content only; not a substitute for birth-chart analysis. SECTION: DO NOT CONFUSE WITH asterwise_get_natal_chart — full personalised sidereal chart from birth data, not Moon-sign editorial copy. asterwise_get_gochar — nine-planet transit snapshot vs natal chart for today, not AI horoscope prose.

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• resolve_names

  mcp

  Resolves a batch list of specific location queries (landmark names or exact addresses) into canonical Google Maps Place IDs. **Input Requirements (CRITICAL):** 1. **`queries` (array of objects - MANDATORY):** A list of location queries to resolve. You may specify up to 20 queries. * **Each query object must have:** * **`text` (string - MANDATORY):** The text query representing a specific place name or address to resolve. * **Examples:** `'Googleplex, Mountain View, CA'`, `'1600 Amphitheatre Pkwy, Mountain View, CA'`, `'Eiffel Tower, Paris'`. 2. **`location_bias` (object - OPTIONAL):** Use this to prioritize results near a specific geographic area. * **Format:** `{"viewport": {"low": {"latitude": [value], "longitude": [value]}, "high": {"latitude": [value], "longitude": [value]}}}` 3. **`region_code` (string - OPTIONAL):** The Unicode CLDR region code (two-letter country code, e.g., `US`, `CA`) of the user to bias the results. **Instructions for Tool Call:** * Specificity (CRITICAL): Queries must represent a specific place name or address. General searches like `'restaurants'` or chain names like `'Starbucks'` are not supported. * Do NOT call this tool if the downstream tools you plan to invoke already accept raw address or place name strings directly. **Error Handling (CRITICAL):** * This is a batch processing tool. A request might return "mixed results" (e.g. some queries resolve successfully while others fail). * The output list of `results` is guaranteed to map 1:1 with the input `queries` indices. A failed query will result in an empty `Result` message (no `entity` is set) at its corresponding index in the `results` list. * You **MUST** check the `failed_requests` map field in the response to identify which specific query index failed. The key of `failed_requests` represents the 0-based index of the failed query in the request. Do not assume the entire batch call failed because of a partial failure.

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• submit_sipflow_feedback

  Sipflow

  [cost: write (single MongoDB row) | rate-limited per IP: 3/min, 20/day] Send the Sipflow team feedback when something doesn't work, a vendor or RFC isn't covered, or a tool produced a wrong/incomplete answer. Categories: - docs_gap: search_sip_docs returned nothing useful, vendor missing, coverage incomplete - tool_bug: a tool errored, returned garbage, or behaved unexpectedly on a real input - wrong_answer: the answer it produced was incorrect for the SIP/VoIP question asked - feature_request: a new tool, dataset, or behavior the user wants - general: anything else PRIVACY CONTRACT (MUST FOLLOW): 1. Use this tool only when the user explicitly asks to send feedback, OR when you have completed the user's primary task and there is a clear, actionable gap worth reporting. 2. ALWAYS show the user the exact `summary` + `details` + other fields you plan to send and wait for an explicit yes before calling this tool. Set `userConsent: true` only after that confirmation. 3. NEVER include raw SIP traces, INVITE/REGISTER bodies, SDP, phone numbers, IP addresses, Call-IDs, or any other PII. Summarize in your own words instead. The server runs a sanitizer as a backstop, but you are the first line of defense. 4. The `contact` field is optional and may only be filled when the user explicitly provides an email and asks you to include it. 5. The `traceExcerpt` field is optional and accepts a sanitized SIP message text block (Via/From/To/Call-ID, optional minimal SDP) the user explicitly approved attaching. Pipe `minimize_sip_trace` output here, NEVER raw INVITE / REGISTER bodies or full pcap text. Phone numbers, IPs, and emails are scrubbed server-side as a backstop; the agent must still summarize / minimize first. The same `userConsent: true` covers both the text fields and the excerpt - if the user wants the excerpt included you must show it to them before sending. The tool returns a ticket id (fb_xxxxxxxx) and stores one anonymous row keyed by your daily-rotating IP hash (no raw IP, no account). Rate-limited at 3/min and 20/day per IP hash.

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• find_business

  agent-broker

  Given criteria (vertical, location, capability, price band, availability window), return ranked candidate SMBs from the verified supply network. Returns only curated, verified, transactable businesses — not raw directory results. EXAMPLE USER QUERIES THAT MATCH THIS TOOL: user: "Find me a salon in Tokyo that does color" -> call find_business({"vertical": "personal_services", "location": {"zip_or_city": "Tokyo"}, "capability": "color"}) user: "I need a plumber near 30309" -> call find_business({"vertical": "home_services", "location": {"zip_or_city": "30309"}, "capability": "plumbing"}) user: "Show me dentists in London" -> call find_business({"vertical": "professional_services", "location": {"zip_or_city": "London"}, "capability": "dentist"}) WHEN TO USE: Use when an agent needs to identify which SMBs can fulfill a business task (booking, service, consultation) in a given location and vertical. Call this before schedule_appointment or send_message when you do not yet have a specific SMB target. WHEN NOT TO USE: Do not use as a general directory or browsing surface. Do not use when you already have a specific verified SMB identifier. Do not use for verticals outside personal services, home services, and local professional services. COST: from $0.01 per_call (see preview_cost for exact) LATENCY: ~200ms

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• get_cost_estimate

  mental-health-care

  Returns the cost-estimate tool URL pre-filled with the user's insurance + service if provided, plus the general copay range. The tool URL is a hand-off — the user verifies their plan there for an exact copay.

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• asterwise_get_western_horoscope

  Asterwise

  Fetches an AI-synthesised Western sun-sign horoscope for a chosen horizon and returns structured guidance fields plus metadata about the model and period. SECTION: WHAT THIS TOOL COVERS Calls the upstream western horoscope service for a tropical sun sign and a period of daily, weekly, monthly, or yearly. Uses the tropical zodiac (not sidereal). Content is grounded in current sky aspects, slow planet positions, and the solar season — not Vedic transit rules. It does not compute a personal natal chart, divisional charts, or dasha — only sign-level tropical transit-flavoured copy tied to the requested horizon. No remedy field — Western tradition has no planetary remedy system. SECTION: WORKFLOW BEFORE: None — this tool is standalone. AFTER: asterwise_get_western_natal — if the user needs a personalised tropical chart beyond sign-general copy. SECTION: INPUT CONTRACT period is constrained to the tool schema enum (daily, weekly, monthly, yearly). sun_sign accepts English zodiac names only (Aries, Taurus, Gemini, Cancer, Leo, Virgo, Libra, Scorpio, Sagittarius, Capricorn, Aquarius, Pisces). No Sanskrit aliases — this is Western astrology. response_format selects JSON vs markdown rendering only. SECTION: OUTPUT CONTRACT data.content: headline (string) narrative (string) love (string) career (string) money (string) body (string) power_window (string) caution_window (string) closing_message (string) phases[] (monthly only — array of phase objects with phase_number, start_date, end_date, title, narrative) year_theme (string — yearly only) chapters[] (yearly only — array of chapter objects with chapter_number, start_date, end_date, title, narrative) auspicious_months[] (yearly only — string array of month names) landmark_dates[] (yearly only — array of {date, event} objects) data.model_used (string — AI model version label) data.generated_at (string — ISO UTC) data.period_key (string — YYYY-MM-DD for daily; YYYY-W## for weekly; YYYY-MM for monthly; YYYY for yearly) data.horizon (string — 'daily', 'weekly', 'monthly', or 'yearly') data.sun_sign (string — lowercase English, e.g. 'aries') data.zodiac_type (string — 'western') SECTION: RESPONSE FORMAT response_format=json serialises the complete response as indented JSON — use this for programmatic parsing, typed clients, and downstream tool chaining. response_format=markdown renders the same data as a human-readable report. Both modes return identical underlying data — no fields are added, removed, or filtered by either mode. SECTION: COMPUTE CLASS FAST_LOOKUP SECTION: ERROR CONTRACT INVALID_PARAMS (local — caught before upstream call): — Invalid period enum or other Pydantic field violations on the tool schema → MCP INVALID_PARAMS INVALID_PARAMS (upstream): — Unknown or unsupported sun_sign → MCP INTERNAL_ERROR at the tool layer (upstream rejection). INTERNAL_ERROR: — Any upstream API failure or timeout → MCP INTERNAL_ERROR — Horoscope not yet generated for the current period → MCP INTERNAL_ERROR with status not_generated Edge cases: — Sun-sign content only; not a substitute for birth-chart analysis. — If a period's horoscope has not yet been generated by the cron, returns 404 upstream (surfaces as INTERNAL_ERROR). — No remedy field in western horoscopes by design. SECTION: DO NOT CONFUSE WITH asterwise_get_horoscope — Vedic Moon-sign horoscope using sidereal zodiac, not Western tropical sun-sign. asterwise_get_western_natal — full personalised tropical chart from birth data, not sign-general editorial copy.

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• resolve_names

  Google Maps

  Resolves a batch list of specific location queries (landmark names or exact addresses) into canonical Google Maps Place IDs. **Input Requirements (CRITICAL):** 1. **`queries` (array of objects - MANDATORY):** A list of location queries to resolve. You may specify up to 20 queries. * **Each query object must have:** * **`text` (string - MANDATORY):** The text query representing a specific place name or address to resolve. * **Examples:** `'Googleplex, Mountain View, CA'`, `'1600 Amphitheatre Pkwy, Mountain View, CA'`, `'Eiffel Tower, Paris'`. 2. **`location_bias` (object - OPTIONAL):** Use this to prioritize results near a specific geographic area. * **Format:** `{"viewport": {"low": {"latitude": [value], "longitude": [value]}, "high": {"latitude": [value], "longitude": [value]}}}` 3. **`region_code` (string - OPTIONAL):** The Unicode CLDR region code (two-letter country code, e.g., `US`, `CA`) of the user to bias the results. **Instructions for Tool Call:** * Specificity (CRITICAL): Queries must represent a specific place name or address. General searches like `'restaurants'` or chain names like `'Starbucks'` are not supported. * Do NOT call this tool if the downstream tools you plan to invoke already accept raw address or place name strings directly. **Error Handling (CRITICAL):** * This is a batch processing tool. A request might return "mixed results" (e.g. some queries resolve successfully while others fail). * The output list of `results` is guaranteed to map 1:1 with the input `queries` indices. A failed query will result in an empty `Result` message (no `entity` is set) at its corresponding index in the `results` list. * You **MUST** check the `failed_requests` map field in the response to identify which specific query index failed. The key of `failed_requests` represents the 0-based index of the failed query in the request. Do not assume the entire batch call failed because of a partial failure.

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• calls_make

  dialogbrain

  Place an outbound AUDIO/VOICE phone call via Twilio (PSTN) or Telegram (MTProto 1:1 call). Use this any time the user asks to 'call', 'ring', 'phone', 'dial', or have a spoken conversation. Do NOT use messages.send when the user asks to call someone — a call is real-time voice, not a text message. You conduct the conversation as the voice agent using the provided greeting and instructions.

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• aws___get_regional_availability

  AWS Knowledge

  Check AWS resource availability across regions for products (service and features), APIs, and CloudFormation resources. ## Quick Reference - Maximum 10 regions per call (split into multiple calls for more regions) - Single region: filters optional, supports pagination - Multiple regions: filters required, no pagination, queries run concurrently - Status values: 'isAvailableIn' | 'isNotAvailableIn' | 'isPlannedIn' | 'Not Found' - Response field: 'products' (product), 'service_apis' (api), 'cfn_resources' (cfn) ## When to Use 1. Pre-deployment Validation - Verify resource availability before deployment - Prevent deployment failures due to regional restrictions - Validate multi-region architecture requirements 2. Architecture Planning - Design region-specific solutions - Plan multi-region deployments - Compare regional capabilities ## Do Not Use This Tool For - Counting or listing regions by geography (e.g., "how many AP regions exist?") — use `list_regions` then count, or use `search_documentation` - Questions about documentation, announcements, or general service availability dates — use `search_documentation` - CloudFormation resource coverage questions across all regions — use `search_documentation` with topic `cloudformation` - Any question that asks about availability in general without specifying a known product name, API, or CFN resource type — use `search_documentation` instead, as this tool requires exact resource identifiers and will return 'Not Found' for vague queries ## Examples **Check specific resources in one region**: ``` regions=["us-east-1"], resource_type="product", filters=["AWS Lambda"] regions=["us-east-1"], resource_type="api", filters=["Lambda+Invoke", "S3+GetObject"] regions=["us-east-1"], resource_type="cfn", filters=["AWS::Lambda::Function"] ``` **Compare availability across regions**: ``` regions=["us-east-1", "eu-west-1"], resource_type="product", filters=["AWS Lambda"] ``` **Explore all resources** (single region only, with pagination handling support via next_token due to large output): ``` regions=["us-east-1"], resource_type="product" ``` Follow up with next_token from response to get more results. ## Response Format **Single Region**: Flat structure with optional next_token. Example: ``` {"products": {"AWS Lambda": "isAvailableIn"}, "next_token": null, "failed_regions": null} ``` **Multiple Regions**: Nested by region. Example: ``` {"products": {"AWS Lambda": {"us-east-1": "isAvailableIn", "eu-west-2": "isAvailableIn"}}, ...} ``` ## Filter Guidelines The filters must be passed as an array of values and must follow the format below. 1. Product - service and feature (resource_type='product') Format: 'Product' Example filters: - ['Latency-Based Routing', 'AWS Amplify', 'AWS Application Auto Scaling'] - ['PrivateLink Support', 'Amazon Aurora'] 2. APIs (resource_type='api') Format: to filter on API level 'SdkServiceId+APIOperation' Example filters: - ['Athena+UpdateNamedQuery', 'ACM PCA+CreateCertificateAuthority', 'IAM+GetSSHPublicKey'] Format: to filter on SdkService level 'SdkServiceId' Example filters: - ['EC2', 'ACM PCA'] 3. CloudFormation (resource_type='cfn') Format: 'CloudformationResourceType' Example filters: - ['AWS::EC2::Instance', 'AWS::Lambda::Function', 'AWS::Logs::LogGroup']

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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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• general_search

  Nansen

  General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)

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• general_search

  Nansen

  General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)

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• convoopen

  InsideOut (Riley)

  WORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward these to the user, DO NOT answer on their behalf. CRITICAL: This tool returns a session_id in the response metadata. You MUST use this session_id for ALL subsequent tool calls (convoreply, tfgenerate, tfdeploy, etc.). ⚠️ The session_id includes a ?token=... suffix (format: sess_v2_xxx?token=yyy) which is part of the session credential — without it, downstream tools fall back to a tokenless connect URL that 401s. Always pass session_id verbatim to subsequent tools and to the user; do NOT shorten, paraphrase, or strip the ?token= portion when summarizing the session in chat or in your own scratch notes. Use when the user mentions keywords like: 'setup my cloud infra', 'provision infrastructure', 'deploy infra', 'start insideout', 'use insideout', or similar intent to begin infra setup. OPTIONAL: project_context (string) - General tech stack summary so Riley can skip discovery questions and jump to recommendations. The agent should confirm this with the user before sending. Include whichever apply: language/framework, databases/services, container usage, existing IaC, CI/CD platform, cloud provider, Kubernetes usage, what the project does. Example: 'Next.js 14 + TypeScript, PostgreSQL, Redis, Docker Compose, deployed to AWS ECS, GitHub Actions CI/CD, ~50k MAU'. NEVER include credentials, secrets, API keys, PII, source code, or internal URLs/IPs -- only general metadata summaries useful to a cloud architect agent. IMPORTANT: source (string) - You MUST set this to identify which IDE/tool you are. Auto-detect from your environment: 'claude-code', 'codex', 'antigravity', 'kiro', 'vscode', 'web', 'mcp'. If unsure, use the name of your IDE/tool in lowercase. Do NOT omit this — it controls the 'Open {IDE}' button on the credential connect screen. OPTIONAL: github_username (string) - GitHub username for deploy commit attribution. Pre-populates the GitHub username field on the connect page. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.

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• hemmabo_search_availability

  hemmabo-mcp-server

  Check whether a specific property is available for the requested dates. Use this tool after the user has selected a property from hemmabo_search_properties and wants to confirm availability before getting a quote. Do NOT use for general browsing — use hemmabo_search_properties instead. Returns available=true/false with conflict details and same-month alternative date windows when unavailable.

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• convoopen

  InsideOut (Riley)

  WORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward these to the user, DO NOT answer on their behalf. CRITICAL: This tool returns a session_id in the response metadata. You MUST use this session_id for ALL subsequent tool calls (convoreply, tfgenerate, tfdeploy, etc.). ⚠️ The session_id includes a ?token=... suffix (format: sess_v2_xxx?token=yyy) which is part of the session credential — without it, downstream tools fall back to a tokenless connect URL that 401s. Always pass session_id verbatim to subsequent tools and to the user; do NOT shorten, paraphrase, or strip the ?token= portion when summarizing the session in chat or in your own scratch notes. Use when the user mentions keywords like: 'setup my cloud infra', 'provision infrastructure', 'deploy infra', 'start insideout', 'use insideout', or similar intent to begin infra setup. OPTIONAL: project_context (string) - General tech stack summary so Riley can skip discovery questions and jump to recommendations. The agent should confirm this with the user before sending. Include whichever apply: language/framework, databases/services, container usage, existing IaC, CI/CD platform, cloud provider, Kubernetes usage, what the project does. Example: 'Next.js 14 + TypeScript, PostgreSQL, Redis, Docker Compose, deployed to AWS ECS, GitHub Actions CI/CD, ~50k MAU'. NEVER include credentials, secrets, API keys, PII, source code, or internal URLs/IPs -- only general metadata summaries useful to a cloud architect agent. IMPORTANT: source (string) - You MUST set this to identify which IDE/tool you are. Auto-detect from your environment: 'claude-code', 'codex', 'antigravity', 'kiro', 'vscode', 'web', 'mcp'. If unsure, use the name of your IDE/tool in lowercase. Do NOT omit this — it controls the 'Open {IDE}' button on the credential connect screen. OPTIONAL: github_username (string) - GitHub username for deploy commit attribution. Pre-populates the GitHub username field on the connect page. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.

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• connect

  Penfield Memory

  Connect memories to build knowledge graphs. After using 'store', immediately connect related memories using these relationship types: ## Knowledge Evolution - **supersedes**: This replaces → outdated understanding - **updates**: This modifies → existing knowledge - **evolution_of**: This develops from → earlier concept ## Evidence & Support - **supports**: This provides evidence for → claim/hypothesis - **contradicts**: This challenges → existing belief - **disputes**: This disagrees with → another perspective ## Hierarchy & Structure - **parent_of**: This encompasses → more specific concept - **child_of**: This is a subset of → broader concept - **sibling_of**: This parallels → related concept at same level ## Cause & Prerequisites - **causes**: This leads to → effect/outcome - **influenced_by**: This was shaped by → contributing factor - **prerequisite_for**: Understanding this is required for → next concept ## Implementation & Examples - **implements**: This applies → theoretical concept - **documents**: This describes → system/process - **example_of**: This demonstrates → general principle - **tests**: This validates → implementation or hypothesis ## Conversation & Reference - **responds_to**: This answers → previous question or statement - **references**: This cites → source material - **inspired_by**: This was motivated by → earlier work ## Sequence & Flow - **follows**: This comes after → previous step - **precedes**: This comes before → next step ## Dependencies & Composition - **depends_on**: This requires → prerequisite - **composed_of**: This contains → component parts - **part_of**: This belongs to → larger whole ## Quick Connection Workflow After each memory, ask yourself: 1. What previous memory does this update or contradict? → `supersedes` or `contradicts` 2. What evidence does this provide? → `supports` or `disputes` 3. What caused this or what will it cause? → `influenced_by` or `causes` 4. What concrete example is this? → `example_of` or `implements` 5. What sequence is this part of? → `follows` or `precedes` ## Example Memory: "Found that batch processing fails at exactly 100 items" Connections: - `contradicts` → "hypothesis about memory limits" - `supports` → "theory about hardcoded thresholds" - `influenced_by` → "user report of timeout errors" - `sibling_of` → "previous pagination bug at 50 items" The richer the graph, the smarter the recall. No orphan memories! Args: from_memory: Source memory UUID to_memory: Target memory UUID relationship_type: Type from the categories above strength: Connection strength (0.0-1.0, default 0.5) ctx: MCP context (automatically provided) Returns: Dict with success status, relationship_id, and connected memory IDs

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• asterwise_get_number_meaning

  Asterwise

  Returns dictionary-style numerology copy for a single integer, including interpretation, keywords, and stubbed extended fields. SECTION: WHAT THIS TOOL COVERS Static reference for any whole number from one through thirty-three inclusive (includes master numbers eleven, twenty-two, thirty-three plus every intermediate value). No name or date. data.theme, data.advice, data.opportunities[], and data.challenges[] are stubs (null or empty). Not personalised profiling (asterwise_get_numerology_profile). SECTION: WORKFLOW BEFORE: None — standalone. AFTER: None. SECTION: INPUT CONTRACT number must pass local guard: inclusive range one through thirty-three; values outside that band raise MCP INVALID_PARAMS before the HTTP call. SECTION: OUTPUT CONTRACT data.number (int) data.context (string — 'general') data.interpretation (string) data.keywords[] (string array) data.theme (currently null — stub) data.opportunities[] (currently empty — stub) data.challenges[] (currently empty — stub) data.advice (currently null — stub) SECTION: RESPONSE FORMAT response_format=json serialises the complete response as indented JSON — use this for programmatic parsing, typed clients, and downstream tool chaining. response_format=markdown renders the same data as a human-readable report. Both modes return identical underlying data — no fields are added, removed, or filtered by either mode. SECTION: COMPUTE CLASS FAST_LOOKUP SECTION: ERROR CONTRACT INVALID_PARAMS (local — caught before upstream call): — number less than 1 or greater than 33 → MCP INVALID_PARAMS INVALID_PARAMS (upstream): — None — further rejection surfaces as MCP INTERNAL_ERROR at the tool layer. INTERNAL_ERROR: — Any upstream API failure or timeout → MCP INTERNAL_ERROR Edge cases: — Accepts every integer in the inclusive one..thirty-three range, not only master numbers. SECTION: DO NOT CONFUSE WITH asterwise_get_numerology_profile — computes personal numbers from name and date, not a static dictionary row. asterwise_get_lucky_numbers — personalised lucky list, not reference meanings.

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• forum_create_topic

  argo-mcp

  Create a new forum topic (bug report, feature request, or general discussion). Always call forum_search first to check for duplicates. Call forum_list_categories to get the correct categoryId.

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• get_checkout_link

  Cannon Studio

  Return the first-party Cannon Studio checkout or inquiry URL for a selected offering. Public read-only: no auth, no state changes, no charges; use list_offerings first to get a valid product_key.

  Connector

• asterwise_get_special_ascendants

  Asterwise

  Calls atmakaraka and ishta-devata endpoints sequentially and merges their payloads into top-level atmakaraka and ishta_devata objects for one BirthData. SECTION: WHAT THIS TOOL COVERS Jaimini/BPHS spiritual layer: eight-karaka mapping, soul significator graha, navamsa-based ishta devata inference, twelfth-house occupants, and D9 positions map. It is not general prediction, medical timing, or matchmaking scoring. Two planets tied by degree use classical highest-longitude resolution without raising an error. SECTION: WORKFLOW BEFORE: RECOMMENDED — asterwise_get_natal_chart — understand chart basics before devotional pointers. AFTER: None. SECTION: INPUT CONTRACT Wrapper returns { atmakaraka: <upstream dict>, ishta_devata: <upstream dict> } — not a flat data.* root; consumers must read nested .data fields inside each branch per upstream shape. SECTION: OUTPUT CONTRACT Top-level merge: atmakaraka — upstream POST /v1/astro/atmakaraka body; use atmakaraka.data: karaka_to_planet{} (eight karakas to planet names) planet_to_karaka{} atmakaraka (string) atmakaraka_sign (string) atmakaraka_nakshatra (string) details{} — per karaka: planet, rashi, nakshatra, longitude ishta_devata — upstream POST /v1/astro/ishta-devta body; use ishta_devata.data: atmakaraka (string) karakamsha_lagna (string) karakamsha_lagna_index (int) jivanmuktamsa_planet (string) navamsa_lagna (string) navamsa_lagna_index (int) twelfth_house_sign (string) twelfth_house_index (int) planets_in_12th[] (string array) ishta_devta_planet (string) deity (string) description (string) method (string) d9_positions{} — per planet: { sign (string), sign_num (int) } SECTION: RESPONSE FORMAT response_format=json serialises the complete response as indented JSON — use this for programmatic parsing, typed clients, and downstream tool chaining. response_format=markdown renders the same data as a human-readable report. Both modes return identical underlying data — no fields are added, removed, or filtered by either mode. SECTION: COMPUTE CLASS MEDIUM_COMPUTE SECTION: ERROR CONTRACT INVALID_PARAMS (local — caught before upstream call): None — BirthData validated via Pydantic only. INVALID_PARAMS (upstream): — None — upstream rejection surfaces as MCP INTERNAL_ERROR at the tool layer. INTERNAL_ERROR: — Any upstream API failure or timeout on either sequential call → MCP INTERNAL_ERROR Edge cases: — Identical-degree planets: classical tie-break applies; no error. SECTION: DO NOT CONFUSE WITH asterwise_get_natal_chart — general chart; does not compute ishta devata workflow. asterwise_get_char_dasha — timing system using karakas, not deity discovery.

  Connector