Step 1 — List all tenants the authenticated user can access. (In the Indicate system a tenant is called a 'space'.)
Returns each tenant's 'id' and 'displayName'.
→ Pass the chosen tenant 'id' as 'tenant_id' to every subsequent tool call.
Connector
166,954 tools. Last updated 2026-06-02 20:00
"Maintaining Consistent Behavior in System Prompts" matching MCP tools:
- Returns the six Fitzpatrick skin types with sun-reactivity behavior and descriptive ancestry hints. Call this when the user's skin type is unknown so you can pick the closest match before calling calculate.Connector
- Delete a knowledge collection. If the collection is assigned to agents, prompts, or channels, pass force=true to delete anyway. CASCADE removes all assignments automatically.Connector
- Lists Vocab Voyage's MCP starter prompts (also exposed via the standard MCP prompts/list endpoint). Useful for hosts that don't yet support prompts/list.Connector
- List all available cat tags for filtering. Use tag names with cat_by_tag to find cats by appearance or behavior.Connector
- Return the Claidex MCP feature map, configured storage/model providers, safety controls, resources, prompts, and tool counts.Connector
Matching MCP Servers
- Alicense-qualityCmaintenanceModel Context Protocol server exposing system prompt files and summaries.Last updated5GPL 3.0
- Alicense-qualityDmaintenanceEnables creation, management, and templating of prompts through a simplified SOLID architecture, allowing users to organize prompts by category and fill in templates at runtime.Last updated27116MIT
Matching MCP Connectors
India Open Government Data (OGD) Platform MCP — data.gov.in
- .promptsOAuth
.prompts, the home to all your AI prompts, everywhere you need them.
- Catch contradictions in reasoning before acting on it. FREE — no account needed. Extracts quantitative and logical claims from any plan, calculation, or chain of thought, then uses a Z3 SAT solver to mathematically prove whether they contradict each other. This is formal verification, not an LLM second-guessing itself. Returns CONSISTENT, CONTRADICTION, or UNKNOWN with the extracted claims.Connector
- Enumerate doc paths in a category/namespace. Use to discover what exists before calling `get_document` or a targeted `grep_docs`. NOT a content search — use `semantic_search` for behavior/concept lookups or `grep_docs` for token lookups. Returns `{path, title, chunks}[]`.Connector
- Generate tabular test fixtures (JSON or CSV) from a chosen mix of fake fields. Each row is a consistent identity — first/last name match the email; state matches the ZIP prefix. Public-domain data tables; pure JS; deterministic when a seed is passed.Connector
- Raw data tool for the LinkedIn grouped weekly report. Do not call this directly for user-facing prompts like 'generate a report', 'show a report', 'dashboard', or 'visual report'; prefer linkedin_render_weekly_group_report so ChatGPT or Claude receives the visual MCP app. Use this only when another tool needs the structured report payload.Connector
- Calculate the recommended inverter size for running AC loads from a DC battery system. Accounts for continuous power, startup surge power (motors typically surge 2-3x), and includes a 25% headroom for the continuous rating. Returns the recommended inverter wattage and the DC current draw at system voltage.Connector
- Author-only newest-first listing of the caller's citation corrections. Filterable by ticker (e.g. all AAPL corrections) or by a single fact_id (returns 0 or 1 row). Pair with `save_citation_override` and `delete_citation_override`. Sample tier rejected. Agent use: call with `ticker` to introspect what corrections the user has previously applied on that ticker — useful for system prompts that respect prior corrections during regeneration.Connector
- Return a focused write-up of the three DRS modeling primitives: Constraint (rate-limiter), Buffer (accumulated state), Interrupt (stoppage). Use this when the user asks specifically about modeling primitives or how to spell a system in DRS. Deterministic text.Connector
- Step 2 — List data sources available within a tenant. (In the Indicate system a data source is called a 'data product'.) Examples: Google Analytics, Facebook Ads, vioma, Booking.com. Returns each data source's 'id', 'displayName', and 'semantic_context_id'. → Pass the chosen 'id' as 'data_source_id' and 'semantic_context_id' to list_metrics.Connector
- Fetch new transcript events from an open Voice Bridge call since the last cursor. Returns partial + final transcripts + system events. Agent should poll in a loop (~500ms-1s). No additional payment.Connector
- Enumerate doc paths in a category/namespace. Use to discover what exists before calling `get_document` or a targeted `grep_docs`. NOT a content search — use `semantic_search` for behavior/concept lookups or `grep_docs` for token lookups. Returns `{path, title, chunks}[]`.Connector
- Fallback/non-widget tool for binding a PromptFax document or one or more HTTPS PDF URLs into the current MCP session before requesting a quote. In ChatGPT widget sessions, prefer the widget's file controls after start_session instead of calling this tool unless the widget is unavailable or the user explicitly asks for fallback behavior.Connector
- Get the name, organization, country, and description for an Autonomous System number. Lightweight version of as_whois.Connector
- Catch contradictions in reasoning before acting on it. FREE — no account needed. Extracts quantitative and logical claims from any plan, calculation, or chain of thought, then uses a Z3 SAT solver to mathematically prove whether they contradict each other. This is formal verification, not an LLM second-guessing itself. Returns CONSISTENT, CONTRADICTION, or UNKNOWN with the extracted claims.Connector
- Returns Layer 3 sanity-check and validation prompts — the 'where AI gets financial modeling wrong' guidance. Use these to audit AI-generated work or catch common modeling errors.Connector