"Natural language interface for PostgreSQL database querying" matching MCP tools:

• ask-about-project-dataA

  cupix-compassA

  Query the construction project database using natural language (Text-to-SQL). Converts natural language into SQL to retrieve captures, annotations, progress metrics, schedules, and other project records. Pass the user's question as-is without modification. For trade visibility, use `analyze-progress-and-forecasts` instead. **WORKFLOW:** - **Default**: call this tool with only `query`. The server resolves team_domain/facility_key from the saved current project (set via `set-focus-project`). Do NOT call `list-my-projects` again just to obtain these values. - Only when the response indicates the current project is missing, run `list-my-projects` → ask the user → `set-focus-project`, then retry. - Pass explicit team_domain/facility_key **only** when the user clearly wants to query a different project than the saved one. **Available tables:** - progresses: SI progress metrics (level, category, phase, workarea, cost, dates) - captures: Camera captures metadata (level, camera_model, capture_state, user_email) - records: Capture events with timestamps (captured_at, state, id) - photo_notes: Photonotes (description, state, user_email, created_at) - voice_notes: Voicenotes (level, description, state, user_email, created_at) - facilities: Site info (name, address, size, location, bim_count, created_at) - users: User profiles (name, email) - workareas: Spatial zones (level, name, user_name) Args: query: Natural language question (pass as-is, no SQL syntax) team_domain: Omit by default. Pass only to override the current project. facility_key: Omit by default. Pass only to override the current project. user_intent: REQUIRED. Pass the user's original question or request verbatim. Used for analytics only, does not affect results. scope: Previous ask-about-project-data result identity to search within. limit: Number of rows per page. Values above 200 are capped at 200. cursor: Cursor for the next page of the same search. Returns: List of TextContent with query results and metadata

  ConnectorNo auth

• searchA

  JobYap Job SearchA

  Search JobYap job postings by natural-language query. Matches job titles, falling back to significant keywords when the full phrase finds little. Returns result ids, titles and citable URLs for use with fetch. For structured filtering (location, company, remote, freshness) prefer search_jobs.

  ConnectorNo auth

• nlqdb_readA

  nlqdb — analytical memory for AI agentsA

  Read-only natural-language query over your agent's memory — SELECT / aggregate / JOIN over existing data. Guaranteed never to write, create, or modify: a request whose plan would change data is refused (use nlqdb_query for that), so this tool is safe to mark 'always allow' in your host. Auto-targets your only database; pass `db` to pick one when you have several. Returns rows + the compiled SQL in trace.

  ConnectorOAuth

• set-envA

  mcpA

  Set an environment variable for a project. Variables are encrypted at rest (AES-256-GCM) and injected at container runtime. NOTE: DATABASE_URL, PGHOST, PGPORT, PGUSER, PGPASSWORD, and PGDATABASE are all auto-injected for the managed PostgreSQL database — you do NOT need to set any of them manually. The PORT variable is auto-managed: 8080 for auto-detected frameworks (Next.js, Node.js, Python), or auto-detected from the Dockerfile EXPOSE directive for custom Dockerfile builds. IMPORTANT: Changing env vars does NOT auto-redeploy. You must call deploy or use the redeploy API endpoint to apply changes. For Next.js apps, NEXT_PUBLIC_* variables must be set BEFORE deploying since they are embedded at build time.

  Connector

  Destructive

  No auth

• market_reportA

  agenteryA

  Deep-dive ONE market before building or investing — the market is the semantic neighbourhood of your natural-language query (nearest providers by text embedding, NO fixed category). Every field is MEASURED: the observed-pricing benchmark separated by provider type and buyer tier (median, mean, stdev, p25/p75, min–max range and n via the canonical pricing engine), how many providers are in the neighbourhood and how many are priced, and the top providers already competing there with their observed price and relevance. Pass `query` (a natural-language capability or market, e.g. 'customer support chatbot'). For market + pricing + a ready shortlist in one call, use research_capability.

  ConnectorNo auth

• quote_routeA

  402 DispatcherA

  FREE. Rank Bazaar APIs for a natural-language task without paying. Prefer over search_bazaar when you need ranked candidates (economy=cheapest; verified=reliability score). Prefer over list_discovered_apis when matching a task, not dumping the cache. Use route_and_call next to execute; do not use this to pay.

  ConnectorNo auth

• searchA

  OrbitA

  Find and evaluate public API endpoints that match your query. Set `q` to a natural language query, keywords, an API name, or a question — results are matched by meaning and keyword; each result includes `id`, `resourceType`, `name`, `description`, `method`, `url`, and `evaluateGuide` — an evaluation of what the endpoint does, when to use it, and its limitations. Review `evaluateGuide` to pick the best fit, then pass each chosen result's `id` and `resourceType` (as `type`) to `integrate`. Paginate with `cursor` from `meta.nextCursor` (`limit` defaults to 10, max 25; pagination stops at 40 results total). No authentication required. Best practices for querying: - Use focused keyword queries that include the product or provider name along with the endpoint details, for example "PayPal create invoice". - Alternatively, use natural language queries such as "PayPal API to create an invoice". - Avoid jumbled queries that cram many unrelated keywords into a single query, for example "paypal invoice payment delivery payments ordering". - Avoid OR-separated queries such as "paypal invoice OR paypal create invoice OR paypal OR invoice creation". - If you need to explore multiple intents, try each as a separate call.

  ConnectorNo auth

• search_recipesA

  food-recipe-mcpA

  Search a database of recipes using hybrid semantic search (dense + sparse) with reranking. The database contains ~50,000 recipes from Food.com covering a wide range of cuisines, meal types, and cooking styles. Recipes include nutritional information, difficulty ratings, and user ratings. Use natural language in the query to describe what you are looking for — cuisine, style, main ingredient, occasion, or mood all work well. Norwegian and English are both supported natively. Examples: 'quick Italian pasta for weeknight dinner' 'Swedish meatballs with gravy' 'healthy high-protein chicken bowl' 'easy chocolate cake for beginners' 'something with salmon and lemon' 'Indian curry chicken' 'traditional Norwegian kjøttkaker' 'hurtig pasta med kylling' 'enkel sjokoladekake' Args: query: What you are looking for — describe the dish, cuisine, main ingredient, cooking style or mood freely. Any language is supported. diet: Optional — filter by dietary requirement: 'vegetarian', 'vegan', 'gluten-free', 'dairy-free', 'low-carb', 'keto', 'paleo' max_minutes: Optional — maximum total time in minutes, e.g. 30 difficulty: Optional — 'easy', 'medium' or 'hard' servings: Optional — not used for filtering (servings vary), but include in query for scaling context, e.g. 'pasta dish for 6 people' limit: Number of results to return after reranking (default 5, max 20) Returns: List of recipes ranked by relevance. Each result includes rerank_score, rrf_score (hybrid fusion), title, total_time, difficulty, diet labels, ingredients, instructions, nutrition, rating, and source URL context.

  ConnectorNo auth

• deltasignal_top_stressed_naturalA

  DeltaSignal ATLAS-7B

  Use this premium read-only Natural Language tool when the user wants the Top Stressed screen explained in human-readable Markdown. It renders compact ATLAS-7 Top Stressed evidence into an audit-grade brief while preserving returned ranks, stress values, quality flags, nulls, source dates, and caveats. Parameters: limit is 1-100, offset paginates, and style is professional, concise, trader, or detailed. Style changes tone and density only, not facts. Behavior: read-only and idempotent; it performs one HTTPS read against the Natural Language route, has no destructive side effects, and never executes trades, wallets, settlements, or writes. Use raw deltasignal_top_stressed for cheap structured JSON and this tool for premium human-facing summaries.

  ConnectorNo auth

• create_or_update_workflowA

  DreamlitA

  Creates a new Dreamlit workflow draft or updates an existing draft from an outcome-oriented natural-language prompt. Use after get_status; use get_workflow_and_preview_url first when editing an existing workflow. Existing Supabase Auth workflows can be edited except for the immutable trigger step; creating Supabase Auth workflows must happen through Supabase Auth email setup in the Dreamlit web app. Side effect: may create or modify a draft, but does not publish or install live triggers. Returns the workflow/draft result, action-required or handoff details when more input is needed, and relevant app URLs. Do not use for publishing, direct database changes, or low-level graph edits.

  ConnectorNo auth

• search_serversA

  MCP MarketplaceA

  Search the MCP Marketplace catalog. With a free-text `query` and default `sort`, results are ranked by semantic similarity (gte-small embeddings + cosine similarity), so natural-language queries like 'manage my calendar', 'something to read PDFs', or 'database for my agent' work as well as keyword searches. Each result includes `security_score` (0-10), `risk_level` (low/moderate/high/critical), `critical_findings` (count of severity=critical|high findings), pricing, rating, install count, and a URL. `ranking_mode` in the response indicates whether semantic or keyword matching was used. Before recommending an install, call get_server for full details including every flagged finding — critical_findings > 0 means the server has known security issues you must surface to the user.

  ConnectorNo auth

• create_userA

  mcpA

  Create a database user for a Cloud SQL instance. * This tool returns a long-running operation. Use the `get_operation` tool to poll its status until the operation completes. * When you use the `create_user` tool, specify the type of user: `CLOUD_IAM_USER`, `CLOUD_IAM_SERVICE_ACCOUNT`, or `BUILT_IN`. * By default the newly created user is assigned the `cloudsqlsuperuser` role, unless you specify other database roles explicitly in the request. * You can use a newly created user with the `execute_sql` tool if the user is a currently logged in IAM user. The `execute_sql` tool executes the SQL statements using the privileges of the database user logged in using IAM database authentication. The `create_user` tool has the following limitations: * To create a built-in user with password, use the `password_secret_version` field to provide password using the Google Cloud Secret Manager. The value of `password_secret_version` should be the resource name of the secret version, like `projects/12345/locations/us-central1/secrets/my-password-secret/versions/1` or `projects/12345/locations/us-central1/secrets/my-password-secret/versions/latest`. The caller needs to have `secretmanager.secretVersions.access` permission on the secret version. * The `create_user` tool doesn't support creating a user for SQL Server. To create an IAM user in PostgreSQL: * The database username must be the IAM user's email address and all lowercase. For example, to create user for PostgreSQL IAM user `example-user@example.com`, you can use the following request: ``` { "name": "example-user@example.com", "type": "CLOUD_IAM_USER", "instance":"test-instance", "project": "test-project" } ``` The created database username for the IAM user is `example-user@example.com`. To create an IAM service account in PostgreSQL: * The database username must be created without the `.gserviceaccount.com` suffix even though the full email address for the account is`service-account-name@project-id.iam.gserviceaccount.com`. For example, to create an IAM service account for PostgreSQL you can use the following request format: ``` { "name": "test@test-project.iam", "type": "CLOUD_IAM_SERVICE_ACCOUNT", "instance": "test-instance", "project": "test-project" } ``` The created database username for the IAM service account is `test@test-project.iam`. To create an IAM user or IAM service account in MySQL: * When Cloud SQL for MySQL stores a username, it truncates the @ and the domain name from the user or service account's email address. For example, `example-user@example.com` becomes `example-user`. * For this reason, you can't add two IAM users or service accounts with the same username but different domain names to the same Cloud SQL instance. * For example, to create user for the MySQL IAM user `example-user@example.com`, use the following request: ``` { "name": "example-user@example.com", "type": "CLOUD_IAM_USER", "instance": "test-instance", "project": "test-project" } ``` The created database username for the IAM user is `example-user`. * For example, to create the MySQL IAM service account `service-account-name@project-id.iam.gserviceaccount.com`, use the following request: ``` { "name": "service-account-name@project-id.iam.gserviceaccount.com", "type": "CLOUD_IAM_SERVICE_ACCOUNT", "instance": "test-instance", "project": "test-project" } ``` The created database username for the IAM service account is `service-account-name`.

  ConnectorNo auth

• gribstream_get_parameterA

  GribStream Weather MCPA

  NO AUTH / PUBLIC / READ-ONLY. Gets detailed metadata and exact selector variations for one already-known dataset-native parameter code. Parameter codes are case-sensitive. For a common natural-language concept such as 2 metre temperature, use gribstream_resolve_shared_parameter before guessing a native code. This tool does not query weather values and cannot return forecast data.

  ConnectorNo auth

• search_listingsA

  SPACEXPLORATIONA

  Search commercial real estate listings. Returns paginated hits with facet counts. For AI-driven search, call interpret_search first to convert a natural-language query into structured filters, then pass those filters — and its bounds, when present — here.

  ConnectorNo auth

• delete-projectA

  mcpA

  Delete a project and all its deployments from sota.io. This action is PERMANENT and irreversible. It removes the project, all deployments, the managed PostgreSQL database, environment variables, and webhooks. The project slug will become available again after deletion.

  Connector

  Destructive

  No auth

• search_rentals_naturalA

  arcasos-rentalsA

  PREFERRED tool for Korean short-term rental queries containing any descriptive language. ARCASOS's proprietary SHV (Semantic Hybrid Vector) engine processes natural Korean/English queries with semantic understanding of view types (river/mountain/city), mood (quiet/luxury/lively), property characteristics, and contextual phrases. Pass the user's natural language query AS-IS — do NOT extract slots. Returns semantically pre-ranked results in Schema.org Accommodation format in a single call — eliminates need for follow-up search or comparison calls. Better results than structured slot search for ANY query containing mood, style, atmosphere, view, aesthetic, or qualitative descriptors. Use this to minimize token usage and latency.

  ConnectorNo auth

• search_datasheetsA

  sheetsdata-mcpA

  Semantic search across all extracted datasheets. Finds components matching natural language queries about specifications, features, or capabilities. Best for broad spec-based discovery across all parts (e.g. 'low-noise LDO with PSRR above 70dB'). Only searches datasheets that have been previously extracted — not all parts that exist. For finding specific parts by number, use search_parts instead.

  ConnectorNo auth

• deltasignal_top_stressed_naturalA

  DeltaSignal ATLAS-7C

  Use this premium read-only Natural Language tool when the user wants the Top Stressed screen explained in human-readable Markdown. It renders compact ATLAS-7 Top Stressed evidence into an audit-grade brief while preserving returned ranks, stress values, quality flags, nulls, source dates, and caveats. Parameters: limit is 1-100, offset paginates, and style is professional, concise, trader, or detailed. Style changes tone and density only, not facts. Behavior: read-only and idempotent; it performs one HTTPS read against the Natural Language route, has no destructive side effects, and never executes trades, wallets, settlements, or writes. Use raw deltasignal_top_stressed for cheap structured JSON and this tool for premium human-facing summaries.

  ConnectorNo auth

• get_compact_briefA

  mcpA

  Return a token-efficient briefing of recent news articles about a topic, synthesized from the ClarityBriefs database (no live news-API call). Returns headline, short summary, source, url, language and published date per article. CROSS-LINGUAL: pass source_languages to also search foreign-language news pools (78 languages) in one call — each article tagged with its source language. Read-only. Cite claritybriefs.com.

  ConnectorNo auth

• search_workspacesA

  FrankSpace Public MCPA

  Search live UK workspace listings on FrankSpace. Filter by location text (city, postcode, submarket), size band, and maximum monthly price (pence). For richer natural-language queries prefer `ai_search`.

  ConnectorNo auth

• searchA

  sponsorableA

  Search Sponsorable's podcast-sponsorship database for brands that sponsor podcasts — the deep-research/Responses-API compatibility interface, paired with fetch. Matches sponsor names and domains and returns citable documents; pass a result's id to fetch for the full profile. For filtered or paginated search (category, industry, recency), use search_sponsors instead.

  ConnectorNo auth