Show columns, types, and row count for a specific table. Call before writing a query.

Search affiliate programs by keyword, category, or commission type

Get a list of all available themes with style descriptions and recommendations. Call this to decide which theme to use. Returns a guide organized by style (dark, academic, modern, playful, etc.) with "best for" recommendations. After picking a theme, call get_theme with the theme name to read its full documentation (layouts, components, examples) before rendering. This tool does NOT display anything to the user — it is for your own reference when choosing a theme.

Inventory mode. List all 18 AXIS programs, their generators, pricing tier, and artifact paths. Free, no auth, and no side effects. Use search_and_discover_tools instead when you only have a keyword, or discover_commerce_tools when you need install and onboarding metadata.

Describe a specific table. ⚠️ WORKFLOW: ALWAYS call this before writing queries that reference a table. Understanding the schema is essential for writing correct SQL queries. 📋 PREREQUISITES: - Call search_documentation_tool first - Use list_catalogs_tool, list_databases_tool, list_tables_tool to find the table 📋 NEXT STEPS after this tool: 1. Use generate_spatial_query_tool to create SQL using the schema 2. Use execute_query_tool to test the query This tool retrieves the schema of a specified table, including column names and types. It is used to understand the structure of a table before querying or analysis. Parameters ---------- catalog : str The name of the catalog. database : str The name of the database. table : str The name of the table. ctx : Context FastMCP context (injected automatically) Returns ------- TableDescriptionOutput A structured object containing the table schema information. - 'schema': The schema of the table, which may include column names, types, and other metadata. Example Usage for LLM: - When user asks for the schema of a specific table. - Example User Queries and corresponding Tool Calls: - User: "What is the schema of the 'users' table in the 'default' database of the 'wherobots' catalog?" - Tool Call: describe_table('wherobots', 'default', 'users') - User: "Describe the buildings table structure" - Tool Call: describe_table('wherobots_open_data', 'overture', 'buildings')

Generate a starter TypeScript intent file from a name and description. Returns a complete defineIntent() source string ready to save as a .ts file — no files are written, no network requests made. On invalid domain values, returns an error string. The output compiles directly with axint.compile. Use this when creating a new intent from scratch; use axint.templates.get for a working reference example, or axint.schema.compile to generate Swift without writing TypeScript.

Search AXIS programs by keyword and return ranked matches with artifact paths. Free, no auth, and no stateful side effects. Example: q=checkout returns commerce-relevant programs first. Use this when you know the outcome you want but not the right program. Use list_programs instead for the full catalog, discover_commerce_tools for install metadata, or discover_agentic_purchasing_needs for purchasing-specific triage.

Discover the best AXIS workflow for a purchasing or compliance task. Free, no auth, and logs lightweight task metadata for intent analytics. Example: task_description='prepare for autonomous Visa checkout'. Use this when you need commerce-specific triage and next-step guidance. Use search_and_discover_tools instead for non-commerce keyword routing across all programs.

Get the builder workflows — step-by-step state machines for building skills and solutions. Use this to guide users through the entire build process conversationally. Returns phases, what to ask, what to build, exit criteria, and tips for each stage.

To help a user register or purchase, call get_activity_details after this — it returns session-level "share_url" links that go directly to checkout. Search children's enrichment activities (camps, classes, after-school programs) by location, age range, date, or keyword. Returns a paginated list with listing-page "url" fields; use slug or id to fetch full details.

Generate Golden Lead packets for B2B sales agents. Cross-references SEC filings, GitHub activity, and job postings to score companies as HOT/WARM/COLD leads with AI pivot signals and recommended outreach angles. Use this tool when: - A sales agent needs to prioritise outreach to companies most likely to buy AI services - You want to detect which companies are actively transitioning to AI and need vendors - A BD agent is building a prospect list with data-backed prioritisation - You need company intelligence that goes beyond basic firmographic data Returns per company: lead_score (HOT/WARM/COLD), ai_pivot_signal, recent_sec_mentions_of_ai, github_ai_repos_added, open_ai_roles, funding_stage, recommended_outreach_angle, key_contacts. Example: getB2bIntel({ companies: ["salesforce", "oracle", "sap"] }) → Salesforce HOT (12 AI roles, $2B AI capex in 10-K), Oracle WARM, SAP COLD. Cost: $5 USDC per call.

Fetch the full column schema for a CDC dataset — names, data types, descriptions, row count, and last-updated timestamp. Essential before writing SoQL queries against unfamiliar datasets.

Get Lenny Zeltser's expert writing guidelines for security reports and assessments. Provides guidance on tone, structure, clarity, executive summaries, and avoiding common writing mistakes. Works for any security document. Your documents are never sent to this server—guidelines flow to your AI for local analysis. Note: For incident response reports specifically, use the ir_* tools which provide deeper section-by-section review criteria.

Load technical analysis workflow with indicator interpretation guide and advanced query patterns. REQUIRES get_database_schema to be called first — this tool has no schema. Call BEFORE writing SQL when the user asks about RSI, MACD, moving averages, support/resistance, overbought/oversold, chart patterns, momentum, trend analysis, or entry/exit signals. Can be combined with other workflow tools.

Get HUD income limits (very low, low, median) by family size. Returns income limit data used to determine eligibility for HUD assisted housing programs. Requires HUD User API token. Args: state: Two-letter US state abbreviation (e.g. 'CA', 'NY'). county_fips: Optional 5-digit county FIPS code (e.g. '06037'). If omitted, returns data for all areas in the state. year: Income limit fiscal year (default 2024).

Get Lenny Zeltser's expert writing guidelines for incident response reports. Topics: tone, words, structure, executive_summary, voice, articles, or summary for quick reference. Your incident data is never sent to this server—guidelines flow to your AI for local analysis.

Update organization settings. Partial update — only provided keys are changed. Pass a settings object with key-value pairs (e.g. {"policies.noShowMaxStrikes": 3, "finances.clientPaymentTiming": "BEFORE"}). All values are validated before writing — if any key fails validation, no changes are applied. Returns the full updated settings for the affected chapters. See settings_get for available keys and valid values.

Load fundamental analysis workflow with advanced query patterns. REQUIRES get_database_schema to be called first — this tool has no schema. Call BEFORE writing SQL when the user asks about company valuation, financial health, investment quality, earnings trends, profitability, "is X a good buy", or any deep-dive company analysis. Can be combined with other workflow tools.

Get full API connection guide for a Japanese SaaS service. Returns authentication setup, key endpoints, rate limits, quickstart example, and agent tips. Use after search_services to learn HOW to connect.

Compile a minimal JSON schema directly to Swift, bypassing the TypeScript DSL entirely. Supports intents, views, widgets, and full apps via the 'type' parameter. Uses ~20 input tokens vs hundreds for TypeScript — ideal for LLM agents optimizing token budgets. Returns Swift source with token usage stats; no files written, no network requests. On invalid input, returns an error message describing the issue. Use this for quick Swift generation without writing TypeScript; use axint.compile when you need the full DSL for complex intents with custom perform() logic.

Compile TypeScript source (defineIntent() call) into native Swift App Intent code. Returns { swift, infoPlist?, entitlements? } as a string — no files written, no network requests. On validation failure, returns diagnostics (severity, AX error code, position, fix suggestion) instead of Swift. Use axint.validate for cheaper pre-flight checks without compilation output; use axint.schema.compile to compile from JSON without writing TypeScript; use axint.scaffold to generate the TypeScript input.

Load fundamental analysis workflow with advanced query patterns. REQUIRES get_database_schema to be called first — this tool has no schema. Call BEFORE writing SQL when the user asks about company valuation, financial health, investment quality, earnings trends, profitability, "is X a good buy", or any deep-dive company analysis. Can be combined with other workflow tools.

Get a comprehensive step-by-step guide for preparing all inputs required for a specific circuit. Read this BEFORE attempting proof generation — the guide covers how to compute signal_hash, nullifier, scope_bytes, merkle_root, how to query EAS GraphQL for the attestation, how to RLP-encode the transaction, how to recover secp256k1 public keys, and how to build the Merkle proof.

Search longform writing across the ATProto network via Planet (planet.filae.site). Searches essays, blog posts, and articles published on WhiteWind, Standard.site/Leaflet, and custom ATProto collections. Returns titles, authors, snippets with highlights.

Search GOV.UK's 700k+ content items using the official Search API. Returns a list of matching content items with title, description, link, format, owning organisation(s), and last updated timestamp. Use filter_format to narrow to specific content types (e.g. 'transaction' for citizen-facing services, 'guide' for guidance, 'publication' for official documents). Use filter_organisations to restrict to a department.

Get detailed information about a specific FEMA disaster declaration. Returns comprehensive data for a single disaster including all declared programs, incident dates, and affected areas. Use disaster numbers from get_disaster_declarations results. Args: disaster_number: The FEMA disaster number (e.g. 4737, 3604).

WHEN: security design, licence audit, or 'what licence does this role require?'. Triggers: 'arborescence du rôle', 'licence nécessaire pour', 'what licence for role', 'role tree', 'droits du rôle', 'entry points of role', 'privilege tree for'. Builds the COMPLETE tree for ONE role: Role -> Duties -> Privileges -> Entry Points. For each entry point, classifies the required D365 licence per the March 2026 Licensing Guide: Team Members (~$8/user/mo, read-only + named tasks), Operations-Activity (~$50, warehouse mobile & production floor), Finance (~$180), Supply Chain Mgmt (~$180), Human Resources (~$22), Project Operations (~$120), Commerce (~$180). Grant-level aware: NoAccess/Read/View -> Team Members; Activity writes -> Operations-Activity; transactional writes -> full product licence based on functional area. Confidence: High (known module prefix) . Medium (keyword) . Low (fallback). Ends with a Optimization section: Team Members / Activity eligibility, role-split opportunities, per-user/month cost estimates (March 2026 MSRP). Always validate against the [Microsoft D365 Licensing Guide](https://go.microsoft.com/fwlink/?LinkId=866544). For a full multi-role scan, call `trace_role_license_tree` multiple times -- once per role. NOT for the pure technical duty/privilege/entry-point chain without licence inference -- use `trace_security_chain` for that.

Get Lenny Zeltser's expert criteria for reviewing an existing IR report. Returns focused guidance for constructive critique — what to check in each section, writing quality issues to identify, and how to frame feedback collaboratively. Your AI uses this to analyze your report locally—your report is never sent to this server.

Retrieve the full agent guide for Decision Anchor. Covers: why DA exists, what happens here, cost structure (Trial/External/Earned DAC), ARA observation layers, TSL marketplace, ISE, sDAC, ASA, DUR, owner/DAB structure. Read this before using DA.

[tourradar] Use this when you need language IDs for filtering tours by guide language. Returns a list of all supported languages with their IDs, codes, and names for use in tour search filters.

Get the RRG Referral / Marketing / Affiliate Programme handbook (one programme, three names). Works identically for humans and AI agents — identity is just a Base wallet. Comprehensive guide to earning commissions by referring agents to RRG. Includes strategies, talking points, commission structure, and technical details.

Returns the full guide for the deBridge MCP server. CALL THIS FIRST.

Semantic (concept-level) search across ATProto longform writing. Uses AI embeddings to find articles by meaning rather than keywords. Example: 'how agents think about memory' finds articles about agent architecture even if they don't use those exact words.

Sales tax, property tax, and investment incentive programs for data centers by US state. Use when: user asks 'tax breaks for a DC in [state]', 'sales tax exemption rules', or evaluates TCO across states. Example: state='VA'. Returns incentive name, eligibility, cap, sunset date, and link to enabling statute. Returns tax credits, property tax abatements, sales tax exemptions, enterprise zones, and incentive programs for data center development. Args: state: US state abbreviation (e.g. 'VA', 'TX', 'OH'). Leave empty for all states summary. Returns: JSON with tax incentive programs, qualifying criteria, and estimated savings.

Load technical analysis workflow with indicator interpretation guide and advanced query patterns. REQUIRES get_database_schema to be called first — this tool has no schema. Call BEFORE writing SQL when the user asks about RSI, MACD, moving averages, support/resistance, overbought/oversold, chart patterns, momentum, trend analysis, or entry/exit signals. Can be combined with other workflow tools.

Get the quickstart guide for the AiPayGen Buyer SDK — install to first paid API call in 60 seconds.

Get usage guide for outtolunch.app — explains available tools, parameters, formats, sections, and best practices for grounding AI responses in current facts.

Builds the schema context for generating BigQuery SQL queries. Returns relevant tables with their fields and semantic definitions. Call this function with the user's question before writing SQL. **IMPORTANT for SQL queries**: Use ONLY the `dataset.table` format (e.g., `prod_google_ads_v2.campaign_stats`). NEVER add a project_id before table names. The `full_name` field of each table already contains the complete name to use in your queries.

Delete STAS plan events in a date window before writing a replacement plan, so old workouts do not remain in the calendar.

Download a free AI agent blueprint by ID. Returns a JSON manifest with all files (SKILL.md, reference docs, implementation guide) ready to write to disk. Same format as the paid Agent Blueprint export.

[$0.001 USDC per call (x402)] US sanctions tracking from OFAC (Office of Foreign Assets Control). Recently added or removed entities, programs, and designations. Powered by PROWL. Use this to answer 'who was recently sanctioned?' or 'are there new sanctions on [country]?'

Sales tax, property tax, and investment incentive programs for data centers by US state. Use when: user asks 'tax breaks for a DC in [state]', 'sales tax exemption rules', or evaluates TCO across states. Example: state='VA'. Returns incentive name, eligibility, cap, sunset date, and link to enabling statute. Returns tax credits, property tax abatements, sales tax exemptions, enterprise zones, and incentive programs for data center development. Args: state: US state abbreviation (e.g. 'VA', 'TX', 'OH'). Leave empty for all states summary. Returns: JSON with tax incentive programs, qualifying criteria, and estimated savings.

List all data collections (lexicon types) stored on a user's ATProto PDS. Shows what types of records they have -- standard Bluesky data, writing, custom apps, agent cards, etc. Useful for discovering what someone has published beyond social posts.

Search cancer support resources in Washington State. Filter by category (housing, food, mental-health, financial, legal, care, transport, children, rights, programs, education), county, tier, or free-text query. Returns matching resources with name, description, phone, URL, eligibility, and cost.

List all authors currently syndicated on Planet, the ATProto longform writing aggregator. Shows handles, display names, and content sources.

Read a PostCopilot blog post / guide about Threads. Returns the full text content. Use postcopilot://blog/catalog resource first to see available guides, or provide a topic to search.

Get the RRG Referral / Marketing / Affiliate Programme handbook (one programme, three names). Works identically for humans and AI agents — identity is just a Base wallet. Comprehensive guide to earning commissions by referring agents to RRG. Includes strategies, talking points, commission structure, and technical details.

Load Lenny Zeltser's IR report writing context for local analysis. Returns expert guidelines for field completeness, incident identification, notification triggers, and writing quality. Your AI uses this context to analyze your incident notes locally—your notes are never sent to this server. Use detail_level to control response size: "minimal" (~2k tokens), "standard" (~5k tokens), or "comprehensive" (~11k tokens).

REST API access for autonomous agents — pricing, quick start, and migration guide. Call this when: building a trading bot, deploying an autonomous agent, hitting rate limits, or running 24/7 without a human in the loop. The MCP tier (what you're using now) is free via Smithery and good for testing. The REST API is for production: pay per call in USDC, no rate limits, no API key required.

Get the SHE Consensus Score and expert verdict for a specific smart home product. The SHE Consensus Score (0-10) is a proprietary metric aggregating reviews from 12 named expert publications (Wirecutter, CNET, PCMag, Tom's Guide, TechRadar, The Verge, etc.). Methodology published at smarthomeexplorer.com/she-score-methodology. Returns score, verdict (Must Buy / Recommended / Good Value / Mixed / Skip), price range, top pros/cons, and the source-linked review page URL with full expert quotes.

List all capabilities and tools available from the Lenny Zeltser's Website MCP server, including search tools and any specialized features like IR report writing assistance.