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205,128 tools. Last updated 2026-06-15 07:24

"A tool for retrieving code examples from GitLab using semantic search" matching MCP tools:

  • Create a DRAFT email campaign via a programmatic wizard. Call this tool and it will guide through the steps — no manual orchestration needed. WIZARD STEPS (handled automatically by the tool): 1. Call with contacts + total_contacts → tool returns engine picker (NextGen vs MyConvo) 2. Add campaign_type from user's click → tool returns campaign category chips (promotional, newsletter, event…) 3. Add campaign_category from user's click → tool returns engine-specific template gallery MyConvo: shows plain_email_templates (personal plain-text). NextGen: shows campaign_templates (HTML). 4. Add template_id from user's pick → tool creates the draft campaign. RULES: Reuse contacts from prior search — never re-search. Pass total_contacts from search result's total_in_crm so the user always sees the full count. Saves as DRAFT only — no emails sent.
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  • Browse the Wix REST API documentation menu hierarchy. Alternative to SearchWixRESTDocumentation - use this to explore and discover APIs by navigating the menu structure instead of searching by keywords. - Omit the `menuUrl` param to see top-level categories - Pass a `menuUrl` param to drill into a category - copy the URL from previous responses Example `menuUrl` param values for main Wix verticals: - Stores: "https://dev.wix.com/docs/api-reference/business-solutions/stores" - Bookings: "https://dev.wix.com/docs/api-reference/business-solutions/bookings" - CMS: "https://dev.wix.com/docs/api-reference/business-solutions/cms" - CRM: "https://dev.wix.com/docs/api-reference/crm" - eCommerce: "https://dev.wix.com/docs/api-reference/business-solutions/e-commerce" - Events: "https://dev.wix.com/docs/api-reference/business-solutions/events" - Blog: "https://dev.wix.com/docs/api-reference/business-solutions/blog" - Pricing Plans: "https://dev.wix.com/docs/api-reference/business-solutions/pricing-plans" - Restaurants: "https://dev.wix.com/docs/api-reference/business-solutions/restaurants" - Media: "https://dev.wix.com/docs/api-reference/assets/media" - Site Properties: "https://dev.wix.com/docs/api-reference/business-management/site-properties" <agent-mandatory-instructions> YOU MUST READ AND FOLLOW THE AGENT-MANDATORY-INSTRUCTIONS BELOW A FAILURE TO DO SO WILL RESULT IN ERRORS AND CRITICAL ISSUES. <goal> You are an agent that helps the user manage their Wix site. Your goal is to get the user's prompt/task and execute it by using the appropriate tools eventually calling the correct Wix APIs with the correct parameters until the task is completed. </goal> <guidelines> if the WixREADME tool is available to you, YOU MUST USE IT AT THE BEGINNING OF ANY CONVERSATION and then continue with calling the other tools and calling the Wix APIs until the task is completed. **Exception:** If the user asks to create, build, or generate a new Wix site/website, skip WixREADME and: - If the user **explicitly** mentions a template, Wix Studio, or headless → call CreateWixBusinessGuide directly. - Otherwise → call the WixSiteBuilder tool directly. **Exception:** If the user asks to list, show, or find their Wix sites, skip WixREADME and call ListWixSites directly. **Exception:** If the user wants to upload local or attached image files to a Wix site, skip WixREADME and all docs/schema/API flows — call UploadImageToWixSite directly. Do NOT use ExecuteWixAPI, SearchWixAPISpec, or any Media Manager REST API for image uploads. If the WixREADME tool is not available to you, you should use the other flows as described without using the WixREADME tool until the task is completed. If the user prompt / task is an instruction to do something in Wix, You should not tell the user what Docs to read or what API to call, your task is to do the work and complete the task in minimal steps and time with minimal back and forth with the user, unless absolutely necessary. </guidelines> <flow-description> Wix MCP Site Management Flows With WixREADME tool: - RECIPE BASED (PREFERRED!): WixREADME() -> find relevant recipe for the user's prompt/task -> read recipe using ReadFullDocsArticle() -> call Wix API using CallWixSiteAPI() based on the recipe - CONVERSATION CONTEXT BASED: find relevant docs article or API example for the user's prompt/task in the conversation context -> call API using CallWixSiteAPI() based on the docs article or API example - EXAMPLE BASED: WixREADME() -> no relevant recipe found for user's prompt/task -> BrowseWixRESTDocsMenu() or SearchWixRESTDocumentation() -> find relevant method -> read method article using ReadFullDocsArticle() to get method code examples -> call API using CallWixSiteAPI() based on the method code examples - SCHEMA BASED, FALLBACK: WixREADME() -> no relevant recipe found for user's prompt/task -> BrowseWixRESTDocsMenu() or SearchWixRESTDocumentation() -> find relevant method -> read method article using ReadFullDocsArticle() -> no method code examples found -> inspect the method schema using SearchWixAPISpec or ReadFullDocsMethodSchema -> call API using CallWixSiteAPI() based on the schema Without WixREADME tool: - CONVERSATION CONTEXT BASED: find relevant docs article or API example for the user's prompt/task in the conversation context -> call API using CallWixSiteAPI() based on the docs article or API example - METHOD CODE EXAMPLE BASED: BrowseWixRESTDocsMenu() or SearchWixRESTDocumentation() -> find relevant method -> read method article using ReadFullDocsArticle() to get method code examples -> call API using CallWixSiteAPI() based on the method code examples - FULL SCHEMA BASED: BrowseWixRESTDocsMenu() or SearchWixRESTDocumentation() -> find relevant method -> read method article using ReadFullDocsArticle() -> no method code examples found -> inspect the method schema using SearchWixAPISpec or ReadFullDocsMethodSchema -> call API using CallWixSiteAPI() based on the schema </flow-description> </agent-mandatory-instructions>
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  • Hybrid search — combines keyword + semantic search via RRF. Uses Reciprocal Rank Fusion (RRF) to merge exact-word results with meaning-based results. **This is the recommended tool for "discourses about X" / concept queries**, because the semantic side catches suttas that discuss a concept using different vocabulary (e.g. some mindfulness-of-breathing suttas use `assasati/passasati/dīghaṁ` instead of `ānāpānassati`). 💡 **Hints for the AI client:** - English queries usually work best (e.g. `mindfulness of breathing`) because the embedding model is multilingual but EN-primary. - Thai stop-word handling is weak. If a Thai query underperforms, the AI client should translate to Pāli/English first (see server instructions). - The default `limit=5` is often too small for a topic survey — use `limit=15-20` (max 20) for good coverage. - Ranking is by similarity, NOT canonical importance — locus classicus suttas (e.g. MN118, DN22) may rank below smaller suttas that happen to use the exact vocabulary. Treat results as a starting point, then call `get_sutta` for the canonical references.
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  • AI-powered company analysis using semantic search over Nordic financial data. Orchestrates multiple searches internally and returns a synthesized narrative answer with source citations. Covers annual reports, quarterly reports, press releases and macroeconomic context for Nordic listed companies. Use this when you want a synthesized answer rather than raw search chunks. For raw data access, use search_filings or company_research instead. For a full due diligence report with AI-planned sections, use the Alfred MCP server: alfred.aidatanorge.no/mcp Args: company: Company name or ticker question: What you want to know about the company model: 'haiku' (default) or 'sonnet'
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  • Browse and filter exploits using STRUCTURED FILTERS ONLY (no free-text query). Use this to filter by source (github, metasploit, exploitdb, nomisec, gitlab, inthewild, vulncheck_xdb, patchapalooza, oscs, poc_monitor), language (python, ruby, etc.), LLM classification (working_poc, trojan, suspicious, scanner, stub, writeup, tool, no_code), author, min stars, code availability, CVE ID, vendor, or product. Also filter by AI analysis: attack_type (RCE, SQLi, XSS, DoS, LPE, auth_bypass, info_leak), complexity (trivial/simple/moderate/complex), reliability (reliable/unreliable/untested/theoretical), requires_auth. NOTE: To search by product name (e.g. 'OpenSSH', 'Apache'), use search_vulnerabilities instead — it has free-text query and get_vulnerability already includes exploits in the response. Examples: source='metasploit' for all Metasploit modules; attack_type='RCE' with reliability='reliable' for weaponizable RCE exploits; cve='CVE-2024-3400' for all exploits targeting a specific CVE; vendor='mitel' for all Mitel exploits.
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  • 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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Matching MCP Servers

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    A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.
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  • GitLab MCP — wraps the GitLab REST API v4 (BYO API key)

  • Corporate travel: search and book flights, hotels, rail and transfers, manage orders.

  • # AWS Documentation Search Tool Use this tool to find relevant AWS documentation — always follow up with `read_documentation` to get complete answers. Prefer this over general knowledge for AWS services, features, configurations, troubleshooting, and best practices. ## When to Use This Tool **Always search when the query involves:** - Any AWS service or feature (Lambda, S3, EC2, RDS, etc.) - AWS architecture, patterns, or best practices - AWS CLI, SDK, or API usage - AWS CDK or CloudFormation - AWS Amplify development - AWS errors or troubleshooting - AWS pricing, limits, or quotas - Strands Agents development - "How do I..." questions about AWS - Recent AWS updates or announcements **Only skip this tool when:** - Query is about non-AWS technologies - Question is purely conceptual (e.g., "What is a database?") - General programming questions unrelated to AWS ## Skill Suggestions for Actionable Queries When your search query matches tasks that benefit from domain-specific expertise, this tool will suggest relevant **Agent Skills**. Skills package domain knowledge, workflows, best practices, decision frameworks, and reference materials that make you a specialist in a particular AWS domain. **How it works:** - Your search query is scored against the skills registry using semantic search over skill descriptions and metadata tags - If your query matches a skill's domain, relevant skills are returned alongside documentation results - Skills cover a wide range of domains: deployment, troubleshooting, security, optimization, architecture, and more - To load a suggested skill, use the `retrieve_skill` tool with the `skill_name` - Once loaded, follow the skill's workflows and retrieve any referenced files as needed **Example queries that may return skills:** - "deploy a web application to AWS" — may return a deployment skill with architecture guidance and step-by-step deployment instructions - "debug Lambda cold start issues" — may return a troubleshooting skill with diagnostic workflows - "secure S3 buckets" — may return a security skill with best practices and compliance checklists - "optimize API Gateway latency" — may return a performance skill with decision frameworks - "set up VPC peering" — may return a networking skill with step-by-step procedures ## Quick Topic Selection | Query Type | Use Topic | Example | |------------|-----------|-------| | API/SDK/CLI code | `reference_documentation` | "S3 PutObject boto3", "Lambda invoke API" | | New features, releases | `current_awareness` | "Lambda new features 2024", "what's new in ECS" | | Errors, debugging | `troubleshooting` | "AccessDenied S3", "Lambda timeout error" | | Amplify apps | `amplify_docs` | "Amplify Auth React", "Amplify Storage Flutter" | | CDK concepts, APIs, CLI | `cdk_docs` | "CDK stack props Python", "cdk deploy command" | | CDK code samples, patterns | `cdk_constructs` | "serverless API CDK", "Lambda function example TypeScript" | | CloudFormation templates | `cloudformation` | "DynamoDB CloudFormation", "StackSets template" | | Architecture, blogs, guides | `general` | "Lambda best practices", "S3 architecture patterns" | | Strands Agents | `strands_docs` | "Strands Agents Python structured output", "Strands Agents AWS CDK EC2 Deployment Example" | | Domain expertise, workflows, guided procedures | `agent_skills` | "deploy serverless app", "debug Lambda cold starts", "secure IAM policies" | ## Documentation Topics ### reference_documentation **For: API methods, SDK code, CLI commands, technical specifications** Use for: - SDK method signatures: "boto3 S3 upload_file parameters" - CLI commands: "aws ec2 describe-instances syntax" - API references: "Lambda InvokeFunction API" - Service configuration: "RDS parameter groups" Don't confuse with general—use this for specific technical implementation. ### current_awareness **For: New features, announcements, "what's new", release dates** Use for: - "New Lambda features" - "When was EventBridge Scheduler released" - "Latest S3 updates" - "Is feature X available yet" Keywords: new, recent, latest, announced, released, launch, available ### troubleshooting **For: Error messages, debugging, problems, "not working"** Use for: - Error codes: "InvalidParameterValue", "AccessDenied" - Problems: "Lambda function timing out" - Debug scenarios: "S3 bucket policy not working" - "How to fix..." queries Keywords: error, failed, issue, problem, not working, how to fix, how to resolve ### amplify_docs **For: Frontend/mobile apps with Amplify framework** Always include framework: React, Next.js, Angular, Vue, JavaScript, React Native, Flutter, Android, Swift Examples: - "Amplify authentication React" - "Amplify GraphQL API Next.js" - "Amplify Storage Flutter setup" ### cdk_docs **For: CDK concepts, API references, CLI commands, getting started** Use for CDK questions like: - "How to get started with CDK" - "CDK stack construct TypeScript" - "cdk deploy command options" - "CDK best practices Python" - "What are CDK constructs" Include language: Python, TypeScript, Java, C#, Go **Common mistake**: Using general knowledge instead of searching for CDK concepts and guides. Always search for CDK questions! ### cdk_constructs **For: CDK code examples, patterns, L3 constructs, sample implementations** Use for: - Working code: "Lambda function CDK Python example" - Patterns: "API Gateway Lambda CDK pattern" - Sample apps: "Serverless application CDK TypeScript" - L3 constructs: "ECS service construct" Include language: Python, TypeScript, Java, C#, Go ### cloudformation **For: CloudFormation templates, concepts, SAM patterns** Use for: - "CloudFormation StackSets" - "DynamoDB table template" - "SAM API Gateway Lambda" - "CloudFormation template examples" ### strands_docs **For: Strands Agents API reference, integrations, model providers, session managers, tools, examples, user-guide** Use for: - "Strands Agents Python SDK example" - "Strands Agents AWS integration" - "Strands Agents community contributions" - "Strands Agents usage examples" - "Strands Agents usage guide" ### general **For: Architecture, best practices, tutorials, blog posts, design patterns** Use for: - Architecture patterns: "Serverless architecture AWS" - Best practices: "S3 security best practices" - Design guidance: "Multi-region architecture" - Getting started: "Building data lakes on AWS" - Tutorials and blog posts **Common mistake**: Not using this for AWS conceptual and architectural questions. Always search for AWS best practices and patterns! **Don't use general knowledge for AWS topics—search instead!** ### agent_skills **For: Discovering agent skills — domain-specific expertise packages for AWS workflows** Use for: - Complex tasks that benefit from guided workflows: "deploy a serverless application" - Troubleshooting scenarios: "debug Lambda cold starts", "resolve ECS task failures" - Security and compliance: "secure S3 buckets", "review IAM policies for least privilege" - Architecture and optimization: "optimize API Gateway latency", "design multi-region architecture" - When you need domain expertise beyond what documentation provides Skills go beyond documentation — they provide workflows, decision frameworks, best practices, and may include embedded procedures for critical sub-tasks. **Important**: This topic is meant for discovery. Once you identify the skill you need, use `retrieve_skill` tool with the `skill_name` to load the full skill and its reference materials. **Note**: If combined with other topics, skills will be mixed into the documentation results. Use `agent_skills` alone for a clean skill-only listing. ## Search Best Practices **Be specific with service names:** Good examples: ``` "S3 bucket versioning configuration" "Lambda environment variables Python SDK" "DynamoDB GSI query patterns" ``` Bad examples: ``` "versioning" (too vague) "environment variables" (missing context) ``` **Include framework/language:** ``` "Amplify authentication React" "CDK Lambda function TypeScript" "boto3 S3 client Python" ``` **Use exact error messages:** ``` "AccessDenied error S3 GetObject" "InvalidParameterValue Lambda environment" ``` **Add temporal context for new features:** ``` "Lambda new features 2024" "recent S3 announcements" ``` **If the first search does not return results that directly answer the question, refine your query and search again with different terms, a more specific phrase, or a different topic. Try conceptual/architectural topics (general, blogs) if reference docs are too narrow.** **After searching, use `read_documentation` on the top-ranked URLs to verify and complete your answer.** ## Multiple Topic Selection You can search multiple topics simultaneously for comprehensive results: ``` # For a query about Lambda errors and new features: topics=["troubleshooting", "current_awareness"] # For CDK examples and API reference: topics=["cdk_constructs", "cdk_docs"] # For Amplify and general AWS architecture: topics=["amplify_docs", "general"] # For actionable tasks: topics=["agent_skills"] ``` ## Response Format Results include: - `rank_order`: Relevance score (lower = more relevant) - `url`: Direct documentation link — use with `read_documentation` to get the full page content - `title`: Page title - `context`: Partial excerpt only — not the complete documentation. After reviewing results, call `read_documentation` on the most relevant URLs before answering. Do not answer based on the context excerpt alone. ## Parameters ``` search_phrase: str # Required - your search query topics: List[str] # Optional - up to 3 topics. Defaults to ["general"] limit: int = 5 # Optional - max results per topic ``` --- **Remember: When in doubt about AWS, always search. This tool provides the most current, accurate AWS information. But search is only step 1 — always read the full documentation to give complete answers.**
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  • Semantic search — match by meaning, not exact words. Uses vector similarity (cosine distance) over `text_pali` embedded with a multilingual MiniLM model. 🤔 **In most cases you should use `search_hybrid` instead** — it combines this semantic search with keyword search and ranks better. Use this tool only when you need: - Pure semantic results (no keyword influence) - Fine-grained `threshold` tuning (hybrid uses RRF which is harder to tune) - To debug what semantic alone picks up vs keyword ⚠️ Known limitations: - The index is **Pāli only** (English/Thai queries pass through the multilingual embedding but the model isn't tuned on Pāli) - English queries usually embed better than Thai (model is EN-primary) - For specific Pāli terms (`appamāda`, `dukkha`), exact match is better — use `search_by_keyword` instead - Pāli stock phrases recur in many suttas → similarity scores cluster; read the top 10, don't trust rank 1 alone
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  • Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use search.files / search.threads / search.links for that.
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  • Scan text or code for leaked secrets: API keys (AWS, GCP, Azure, OpenAI, Anthropic, Stripe, GitHub, GitLab, Slack, Twilio, SendGrid, HuggingFace), private keys (RSA/EC/PGP), JWTs, database connection strings, Bearer tokens, and Basic auth headers. Returns a list of findings with type, severity, line number, and a redacted preview. Use before committing code, sharing logs, or sending text to an LLM. 100% regex-based, zero network calls.
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  • Find a creator by name/handle, while preserving legacy semantic creator search. Use this as the default creator lookup tool when the user gives a creator-ish string but not a canonical creator UUID: a handle, partial handle, display name, creator name, or profile-ish text. This is cheap, fast, and backed by the creator lookup index. If the user gives an exact handle on a specific platform (for example "@niickjackson on Instagram"), prefer `get_profile` first because it returns the full platform profile. If you need to resolve a rough creator name or partial handle first, use this tool with `query_type: "creator_lookup"`. For backward compatibility, this tool still accepts the old semantic-search fields (`platforms`, follower/engagement filters, `creator_kinds`) and routes legacy calls to the semantic endpoint unless the query clearly contains a handle/profile URL. For new topical/niche discovery calls such as "fitness creators in NYC" or "vegan recipe creators with high engagement", prefer `semantic_search_creators` because its name is explicit and less likely to be confused with exact creator lookup. Examples: - User: "Find @cris" -> use this tool with query "cris" and query_type "creator_lookup". - User: "Who is that fitness coach called Jane?" -> use this tool with query "Jane" and query_type "creator_lookup". - User: "Pull @niickjackson on Instagram" -> use `get_profile` with platform "instagram" and username "niickjackson". - User: "Find news creators with 1M+ followers" -> use `semantic_search_creators`, not this tool. Returns either autocomplete-style creator lookup results or legacy semantic results, depending on routing. Use returned creator IDs with `get_creator`, `find_lookalike_creators`, or `match_creators`; use returned platform usernames with `get_profile` or `get_posts`.
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  • 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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  • 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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  • Look up country-specific payment codes (KNP, purpose codes, etc.). Use country_banking_rules first to see which code types a country requires (in the payment_requirements block), then use this tool to find the right code value. Args: country_code: ISO 3166-1 alpha-2 (e.g., "KZ", "AE") code_type: Code table to search (from payment_requirements required_fields[].code_type, e.g., "knp", "purpose_code") search: Optional keyword filter (e.g., "transport", "trade", "insurance") Examples: country_payment_codes("KZ", "knp", "transport") country_payment_codes("KZ", "knp", "insurance") country_payment_codes("AE", "purpose_code", "trade") country_payment_codes("KZ", "knp") # all codes (large response)
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  • ⚠️ MANDATORY FIRST STEP - Call this tool BEFORE using any other Canvs tools! Returns comprehensive instructions for creating whiteboards: tool selection strategy, iterative workflow, and examples. Following these instructions ensures correct diagrams.
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  • Discovers the most relevant tools available on this MCP server for a given task using local semantic search (MiniLM-L6-v2 embeddings). Accepts a plain-English description of what needs to be accomplished and returns the best matching tools ranked by relevance, along with their input schemas, pricing tier, and exact call instructions. Use this tool first when you are connected to this server but do not know which specific tool to call — describe your goal and let platform_tool_finder identify the right capability. Do not use this tool if you already know the tool name — call that tool directly instead. Returns up to 10 results ranked by semantic similarity score.
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  • 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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  • Resolve free-text like "Las Vegas" or "Mallorca" into the canonical shape every other PriceTik tool needs — hotel-search-friendly text, the Hotelbeds activity destination code for pricetik_activity_search, country, and a subtitle. Agents call this first so they never have to ask the user for a destination code. Cache-backed, no API key required.
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  • Semantic discovery search for influencers/content creators using natural-language queries. Use this only when the user asks to discover creators by topic, audience, geography, niche, content style, or campaign criteria (e.g., "fitness creators in NYC", "vegan recipe creators with high engagement", "tech reviewers who cover phones"). The query is matched against creator profiles, extracted facts, and visual style via hybrid vector search. Do not use this for exact handles, usernames, or known creator names. If the user gives a specific platform and handle (for example "@niickjackson on Instagram"), use `get_profile` first. For rough name/handle lookup, use `search_creators`. For multiple known handles, use `lookup_profiles`. Semantic search can return lookalike or topical matches and is allowed to miss an exact username. Examples: - User: "Find news creators with 1M+ followers" -> use this tool. - User: "Find creators in LA who make cinematic travel videos" -> use this tool. - User: "Pull @niickjackson on Instagram" -> use `get_profile`, not this tool. - User: "Is @niickjackson a fit for Pixel?" -> use `get_profile` first, optionally `get_posts`, then `match_creators`. Returns a ranked list of creators (id, platform, username, follower count, engagement rate, top categories, evidence facts). Use the flat follower, engagement-rate, and verified fields to constrain results when the user gives concrete numeric constraints. Use `find_lookalike_creators` instead when you want creators SIMILAR to known ones. Use `match_creators` when you want to SCORE specific creators against a brief.
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  • Semantic search across the user's entire library by meaning, theme, or vibe. Searches every book/movie/album/show/anime as one corpus. Use for cross-media or thematic questions like "things about grief" or "noir mood". For specific title/creator lookups, use the keyword `search` tool instead.
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