"Natural Language to SQL Conversion Tools or Resources" matching MCP tools:

• deltasignal_top_stressed_natural

  DeltaSignal ATLAS-7

  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.

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• search_knowledge

  AlgoVault — Crypto Quant Trade Calls

  Ask AlgoVault any question about its MCP tools, response shapes, integration patterns (LangChain / LlamaIndex / MAF / CrewAI), or code examples. Returns ranked snippets from the canonical knowledge bundle. Use this BEFORE attempting any tool call to confirm correct parameter usage and avoid hallucinating tool shapes. Fast (BM25 lexical search, no LLM call, no quota cost). For natural-language synthesized answers, use chat_knowledge instead.

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• edit_image

  Sats4AI - Bitcoin-Powered AI Tools

  Edit an image with natural language instructions. Uses Nano Banana 2 — understands context, handles object addition/removal, style transfer, and inpainting. Returns JSON with image URL. Resolution-tiered pricing: 1K=200 sats, 2K=300 sats, 4K=450 sats. Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='edit_image' and resolution param.

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• import_data

  mcp

  Import data into a Cloud SQL instance. If the file doesn't start with `gs://`, then the assumption is that the file is stored locally. If the file is local, then the file must be uploaded to Cloud Storage before you can make the actual `import_data` call. To upload the file to Cloud Storage, you can use the `gcloud` or `gsutil` commands. Before you upload the file to Cloud Storage, consider whether you want to use an existing bucket or create a new bucket in the provided project. After the file is uploaded to Cloud Storage, the instance service account must have sufficient permissions to read the uploaded file from the Cloud Storage bucket. This can be accomplished as follows: 1. Use the `get_instance` tool to get the email address of the instance service account. From the output of the tool, get the value of the `serviceAccountEmailAddress` field. 2. Grant the instance service account the `storage.objectAdmin` role on the provided Cloud Storage bucket. Use a command like `gcloud storage buckets add-iam-policy-binding` or a request to the Cloud Storage API. It can take from two to up to seven minutes or more for the role to be granted and the permissions to be propagated to the service account in Cloud Storage. If you encounter a permissions error after updatingthe IAM policy, then wait a few minutes and try again. After permissions are granted, you can import the data. We recommend that you leave optional parameters empty and use the system defaults. The file type can typically be determined by the file extension. For example, if the file is a SQL file, `.sql` or `.csv` for CSV file. The following is a sample SQL `importContext` for MySQL. ``` { "uri": "gs://sample-gcs-bucket/sample-file.sql", "kind": "sql#importContext", "fileType": "SQL" } ``` There is no `database` parameter present for MySQL since the database name is expected to be present in the SQL file. Specify only one URI. No other fields are required outside of `importContext`. For PostgreSQL, the `database` field is required. The following is a sample PostgreSQL `importContext` with the `database` field specified. ``` { "uri": "gs://sample-gcs-bucket/sample-file.sql", "kind": "sql#importContext", "fileType": "SQL", "database": "sample-db" } ``` The `import_data` tool returns a long-running operation. Use the `get_operation` tool to poll its status until the operation completes.

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• answer_permit_question

  kolmo-mcp-server

  Grounded permit Q&A for a specific Seattle-area address. Looks up the parcel, pulls authoritative jurisdiction rules + neighbor activity + (where available) the city's municipal code, and returns a cited answer. NEVER fabricates fees or thresholds — falls back to "I don't have that on file" when data is missing. Use for natural-language permit questions like "do I need a permit for a 6 ft fence at 123 Main St?" or "what permits does an ADU at this address require?"

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• updateCampaignGoals

  NotFair-GoogleAds

  Switch a campaign between campaign-specific and account-level conversion goals. Set to CUSTOMER to use account-level goals (required before switching to non-conversion bidding strategies like MAXIMIZE_CLICKS or MANUAL_CPC). Set to CAMPAIGN for campaign-specific goals. Note: updateCampaignBidding auto-handles this when switching to MAXIMIZE_CLICKS or MANUAL_CPC, so this tool is only needed for manual goal config changes.

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• search_blog

  self-hosted-ai

  Search the Sovereign AI Blog for articles matching a natural language query, optionally filtered by tag and sorted by relevance or date. Behaviour matrix: - query='', sort=* -> list newest-first, optionally tag-filtered - query!='', sort=relevance -> TF-IDF ranked, optionally tag-filtered - query!='', sort=date_desc -> TF-IDF filtered (score > 0.001), then sorted by date Pure read-only, deterministic for a given KB snapshot.

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• search_datasheets

  sheetsdata-mcp

  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.

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• check_credit_balance

  mdmagic

  Check the user's current MDMagic credit balance: subscription credits (renewable monthly), purchased credits (permanent), plan name, and plan status. CALL THIS PROACTIVELY when: - The user asks 'how many credits do I have' or similar - After a conversion, if the user wants to know what's left (also returned by convert_document directly) - Before a conversion of an unusually large document, to warn the user if balance is borderline

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• deltasignal_top_stressed_natural

  DeltaSignal ATLAS-7

  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.

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• estimate_conversion_cost

  mdmagic-mcp-server

  Estimate credit cost for a conversion BEFORE running it. Returns word count, page calculation (300 words/page), and a credit breakdown by format and template type. Use this when the user asks 'how much will this cost?' or when you suspect a conversion might exceed their balance — convert_document refuses to run if credits are insufficient, so estimating first is friendlier.

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• get_query_patterns

  Shibui Finance

  REQUIRED before stock_data_query, 19 SQL patterns prevent timeouts/wrong results Must be called once per session immediately after get_database_schema. Contains query patterns for time-series selection, return calculations, screening joins, window functions, backtesting, and performance optimization. Time-series queries will timeout or return wrong results without these patterns. After this tool returns, call stock_data_query to execute SQL.

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• estimate_conversion_cost

  mdmagic

  Estimate credit cost for a conversion BEFORE running it. Returns word count, page calculation (300 words/page), and a credit breakdown by format and template type. Use this when the user asks 'how much will this cost?' or when you suspect a conversion might exceed their balance — convert_document refuses to run if credits are insufficient, so estimating first is friendlier.

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• deltasignal_morning_brief_natural

  DeltaSignal ATLAS-7

  Use this premium read-only Natural Language tool when the user wants the server-composed Morning Brief rendered as audit-grade Markdown. It compiles backend-composed compact evidence across readiness, daily changes, risk distribution, top stressed issuers, and alpha opportunities. The renderer never fans out into tools and never generates social drafts or trade recommendations. Parameters: style is professional, concise, trader, or detailed. Date and limit are accepted only where the backend composite supports them. Behavior: read-only and idempotent; it performs the server-enforced Morning Brief workflow, has no destructive side effects, then renders the returned compact evidence as a bounded Natural Language response.

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• check_credit_balance

  mdmagic-mcp-server

  Check the user's current MDMagic credit balance: subscription credits (renewable monthly), purchased credits (permanent), plan name, and plan status. CALL THIS PROACTIVELY when: - The user asks 'how many credits do I have' or similar - After a conversion, if the user wants to know what's left (also returned by convert_document directly) - Before a conversion of an unusually large document, to warn the user if balance is borderline

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• deltasignal_covenant_stress_natural

  DeltaSignal ATLAS-7

  Use this premium read-only Natural Language tool when the user wants ticker-specific covenant stress evidence explained in human-readable Markdown. It renders compact ATLAS-7 covenant, leverage, liquidity, filing, and stress evidence into an audit-grade brief while preserving returned ticker, issuer, values, source dates, nulls, quality flags, and caveats. Parameters: ticker is required; date is optional and maps to the evidence period when supported; style is professional, concise, trader, or detailed. Behavior: read-only and idempotent; it performs one HTTPS read against the Natural Language route, has no destructive side effects, and never infers covenant breach, default risk, insolvency, liquidity crisis, or trade direction unless returned by evidence.

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• get_free_resources

  Makuri Showcase (CogniLedger)

  Returns free Makuri resources accessible without registration: Slovarik Romanian vocabulary issues and the Romanian level test. Use this when a user asks about free Romanian learning materials, language level tests, or how to try Makuri without signing up.

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• principles.list

  AI Design Blueprint

  List all 10 Blueprint principles with stable slugs, titles, and clusters. Use this when you need the full inventory or want every principle in one cluster (pass cluster slug to filter). Prefer principles.search when the user describes a topic, failure mode, or keyword in natural language. Prefer principles.get when you already know the exact slug and need full detail.

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• search_rentals_natural

  arcasos-rentals

  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.

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• bible.search.semantic

  Urantia Papers

  Free-form natural-language search across all Bible chunks, ranked by cosine similarity. Each result includes the top-N pre-computed Urantia paragraphs related to that chunk via `bible_parallels` (direction=bible_to_ub). One query surfaces both Bible matches and the relevant UB content. Optional filters: `canon` (`ot`, `deuterocanon`, `nt`) and `book_code`. Set `urantia_parallel_limit` to 0 to suppress the UB attachment. Requires OPENAI_API_KEY.

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