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675,998 tools. Updated 2026-10-19 09:48

"Tools and techniques for analyzing and manipulating databases" matching MCP tools:

  • Return canonical synthesis / patching techniques with role-keyed module realizations drawn from the corpus. Use this when the user asks "how do I do X?" with X being a recognisable technique (low-pass-gate plucks, pinged-filter percussion, parallel multiband processing, complex-oscillator FM, karplus-strong pluck, clocked-delay feedback, modal-resonator excitation, wavefolder harmonics, envelope-follower ducking, Maths-style function-generator omnibus). It's also the right tool when the user has a module and asks "what's this good for?" — pass filter.module_id to retrieve every technique that references the module via its role_realizations. Each technique declares role_definitions (the roles the technique uses, each with required and optional affordances) and role_realizations (concrete modules that fill each role, with the affordances they provide). The model substitutes modules from the user's rack into roles by affordance match — DO NOT treat the realization list as exhaustive or as a recipe. Args: - filter (optional): { capability?, module_id?, text? } - capability: kebab-case capability id (see search_modules _meta.taxonomy). Returns techniques whose required *or* optional capability list includes this id. - module_id: "<manufacturer>/<module-slug>". Returns techniques that have a role_realization referencing this module. - text: free-text phrase. Substring-matches against technique id/label/description AND a curated alias table (technique_aliases) — that's the right surface when a user types evocative prose like "stuttering delay", "plucked string", "source of uncertainty" that doesn't grep against any kebab-case id. Two-way alias match: long alias ("source of uncertainty") matches short query ("uncertainty"), and vice versa. - When multiple filters supplied, AND-intersects. - Omit filter entirely to list all techniques. Returns: { "techniques": [ { "id": "low-pass-gate-pluck", "label": "Low-Pass Gate Pluck", "description": "Send a short envelope...", "required_capabilities": ["lowpass-gate"], "optional_capabilities": ["envelope-generator", "function-generator"], "role_definitions": [ { "role_id": "lpg", "description": "The vactrol-based or vactrol-emulating element. Strictly required...", "required_affordances": ["lowpass-gate"], "optional_affordances": [] }, ... ], "role_realizations": [ { "role_id": "lpg", "module_id": "make-noise/optomix", "affordances_provided": ["lowpass-gate"], "notes": "Two-channel vactrol-based LPG..." }, ... ], "canonical_instance": { "rationale": "...", "lineage": [ { "position": 1, "label": "Buchla 292 (1970)", "module_id": null, "notes": "..." }, { "position": 2, "label": "Tiptop Audio Buchla 292t", "module_id": "tiptop-audio/buchla-292t" }, ... ] }, "counter_canonical_notes": [ { "claim_pushed_back_against": "Optomix is the canonical pairing with Plaits...", "evidence": "The corpus catalogs 19 LPG-capable modules..." } ], "coverage": [ { "role_id": "voice", "realizations_count": 3 }, { "role_id": "lpg", "realizations_count": 19 }, { "role_id": "env", "realizations_count": 6 }, { "role_id": "clock", "realizations_count": 2 } ] } ], "_meta": { "filter": {...}, "feedback_hint"?: string } } How to use role data: - role_realizations are CURATORIAL SAMPLES, not exhaustive lists. The coverage[].realizations_count tells you how many are documented; other modules may fill the same role. - To find modules in the user's rack that can fill a role, use find_role_realizations(technique_id, role_id, available_modules). - canonical_instance is opt-in and sparse. Most techniques don't have one; that absence is information. When present, it documents a documented historical lineage (e.g., Buchla 292 → 292t → MMG → Optomix for low-pass-gate-pluck) — NOT a prescription. - counter_canonical_notes push back on likely training-data priors. When the user invokes a canonical-sounding claim that has a counter_canonical_note, surface the pushback. Errors: - "Module not found: <id>" if filter.module_id is supplied and unknown. - Empty techniques[] with a feedback_hint when filters produce no matches — call report_gap if the user expected coverage.
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  • Search the MITRE ATLAS catalog of AI/ML attack techniques by keyword, tactic, or maturity. Default response is SLIM (description truncated to 240 chars per row); pass include='full' for the verbose record. Pass exclude_id when chaining from atlas_technique_lookup to skip self in sibling-tactic searches. Use this to discover techniques matching a threat-model question, e.g. 'what techniques target LLM serving infrastructure?'. Drill into atlas_technique_lookup with any returned technique_id for the full description, ATT&CK bridge, and pivot hints. For broader cross-referencing: when a result has attack_reference_id, that bridges to D3FEND mitigations via d3fend_defense_for_attack. Free: 30/hr, Pro: 500/hr. Returns {query (echoed filters), total, results [{technique_id, name, description (truncated by default), tactics, inherited_tactics, maturity, attack_reference_id, subtechnique_of}], next_calls}.
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  • Get USER PROFILES of people who interacted with an Instagram post. Returns full user data (bio, followerCount, followingCount, etc.). RETURNS USER PROFILES: id, username, fullName, biography, followerCount, followingCount, isVerified, profilePicUrl. Use for analyzing WHO engaged with a post. NOT FOR COMMENT TEXT: To read the actual comment content (what people wrote), use getInstagramCommentsByPostId instead. INTERACTION TYPES: "commenters" (users who commented), "likers" (users who liked). WHEN TO USE THIS TOOL: Analyzing commenters/likers demographics, finding influencers who engaged, building audience profiles, network analysis of who interacts with posts. WHEN TO USE getInstagramCommentsByPostId: Reading comment text, sentiment analysis of what was said, analyzing discussion content. FAST (default, omit responseType or responseType="fast"): Returns up to 300 results directly (use limit param to reduce, e.g. limit=5). Auto API fallback for commenters when stale. PAGING (responseType="paging"): Async paginated results (1000 users per page with default fields), returns operationId - IMMEDIATELY call checkOperationStatus to get results. CSV export included via dataDumpExportOperationId. Supports pageNumber/tableName for subsequent pages. Optional fields (default: ["id", "username", "fullName"]). Available: biography, isPrivate, isVerified, followerCount, followingCount, mediaCount, profilePicUrl. This is a safe, read-only tool for analyzing searchable information.
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  • List the SQL databases (D1 or Neon Postgres) on my account, including which owned site (if any) each is attached to. Call this BEFORE db_query/db_schema-style work to discover a databaseId — those live on a per-database MCP server reached via GET /api/v1/databases/{id} (see llms.txt), which this id feeds.
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  • Check the status of a submitted job. Call this after submit_query to see if your job is ready. Status progression: submitted -> analyzing -> fetching -> clustering -> enriching -> completed/failed IMPORTANT: Jobs take several minutes to process. First check after ~1-2 minutes, then poll every 30-60 seconds. Broad searches can take 10-30+ minutes; for long jobs, poll every 60-120 seconds. Do NOT call this tool in a tight loop. Stop polling when status is `completed` or `failed`. Treat `submitted`, `analyzing`, `fetching`, `clustering`, and `enriching` as active states and continue polling. You don't need to wait for completion to pull results. Partial results are available during `enriching` — call pull_results after ~2 minutes, then poll status every 30-60 seconds and pull again for fresher results. Do not stop pulling just because an intermediate pull is empty/unchanged. Use `progress_validated` vs `candidate_records` to track whether more results may still appear (`progress_validated < candidate_records`). If transport/session fails, resume using the same `job_id`.
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  • Check the status of a submitted job. Call this after submit_query to see if your job is ready. Status progression: submitted -> analyzing -> fetching -> clustering -> enriching -> completed/failed IMPORTANT: Jobs take several minutes to process. First check after ~1-2 minutes, then poll every 30-60 seconds. Broad searches can take 10-30+ minutes; for long jobs, poll every 60-120 seconds. Do NOT call this tool in a tight loop. Stop polling when status is `completed` or `failed`. Treat `submitted`, `analyzing`, `fetching`, `clustering`, and `enriching` as active states and continue polling. You don't need to wait for completion to pull results. Partial results are available during `enriching` — call pull_results after ~2 minutes, then poll status every 30-60 seconds and pull again for fresher results. Do not stop pulling just because an intermediate pull is empty/unchanged. Use `progress_validated` vs `candidate_records` to track whether more results may still appear (`progress_validated < candidate_records`). If transport/session fails, resume using the same `job_id`.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.
    AGPL 3.0
  • A
    license
    Not graded
    quality
    D
    maintenance
    Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.
    1
    GPL 3.0

Matching MCP Connectors

  • Rick and Morty MCP — wraps the Rick and Morty API (free, no auth)

  • Decision Layer for AI Agents — 58+ tools, Advisor, MCP. Free key: POST /v1/register {}.

  • Browse Statistics Estonia's (Statistikaamet) statistics database tree by path. Top-level databases: keskkond (environment), majandus (economy), rahvastik (population: migration, births/deaths, family), sotsiaalelu (social life: labour market, education, health), eri-valdkondade-statistika (multidomain statistics), rahvaloendus (population and housing census), Lepetatud_tabelid (discontinued datasets). Returns child nodes (subcategories, type=l) or table descriptors at leaf nodes (type=t). Use empty path '' to get the top-level databases. Navigate hierarchically until type=t nodes appear, then use estonia-statistics.table_metadata. Data: andmed.stat.ee (PXWeb API), no auth required.
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  • Get COMMENT CONTENT (text, likes) for an Instagram post. Returns the actual comment objects with text and metadata. RETURNS COMMENT DATA: id, text, username, createdAtDate, likeCount, childCommentCount. Use for reading what people said. NOT FOR USER PROFILES: To get detailed user profiles (bio, followerCount, followingCount) of commenters, use getInstagramPostInteractingUsers with interactionType="commenters" instead. IMPORTANT: postId must be in strong_id format (e.g., "3606450040306139062_4836333238") - use the full "id" value from other Instagram tools, NOT just the media_id. FAST (default, omit responseType or responseType="fast"): Returns up to 300 results directly (use limit param to reduce, e.g. limit=5). Auto API fallback for fresh data. PAGING (responseType="paging"): Async paginated results (100/page), returns operationId for polling via checkOperationStatus. Supports pageNumber/tableName for subsequent pages. CSV (responseType="csv"): Async single CSV download, returns operationId, poll for S3 link. CODE EXECUTION: For csv mode, download CSV and use code execution to analyze full dataset. Ideal for: sentiment analysis, reading discussions, analyzing comment content, engagement patterns. Date filters: OMIT startDate/endDate parameters by default. ONLY pass these if user explicitly requests specific date range (YYYY-MM-DD format). IMPORTANT!!!!!: THE CURRENT YEAR IS 2026. When user requests relative dates (last week, last month), verify the current date from your system context and double-check the calculated dates - models often get the year wrong, searching one year earlier than intended. Optional fields: ["id", "text", "username", "createdAtDate", "likeCount"]. This is a safe, read-only tool for analyzing searchable information.
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  • Get COMMENT CONTENT (text, likes) for a Tiktok post. Returns the actual comment objects with text and metadata. RETURNS COMMENT DATA: id, text, username, createdAtDate, likeCount. Use for reading what people said. FAST (default, omit responseType or responseType="fast"): Returns up to 300 results directly (use limit param to reduce, e.g. limit=5). Auto API fallback for fresh data. PAGING (responseType="paging"): Async paginated results (100/page), returns operationId for polling via checkOperationStatus. Supports pageNumber/tableName for subsequent pages. CSV (responseType="csv"): Async single CSV download, returns operationId, poll for S3 link. CODE EXECUTION: For csv mode, download CSV and use code execution to analyze full dataset. Ideal for: sentiment analysis, reading discussions, analyzing comment content, engagement patterns. Date filters: OMIT startDate/endDate by default. ONLY pass if user explicitly requests date range. IMPORTANT!!!!!: THE CURRENT YEAR IS 2026. When user requests relative dates (last week, last month), verify the current date from your system context and double-check the calculated dates - models often get the year wrong, searching one year earlier than intended. Optional fields: ["id", "text", "username", "createdAtDate", "likeCount"]. This is a safe, read-only tool for analyzing searchable information.
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  • Search detailed documentation for Strudel live coding or ABC/ABCJS notation. Returns relevant code examples and explanations from the official docs. Use this when the curated guides (get-strudel-guide, get-music-guide) don't cover what you need — for specific functions, advanced techniques, or when you're unsure about syntax. Powered by semantic search over strudel.cc and ABCJS docs.
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  • CATALOG of the databases raw SQL can reach — the SHOW DATABASES equivalent. For each database: what it holds, which tool runs SQL against it, how to see its tables, and which specialized tools answer the same questions without SQL. Call it before writing raw SQL against an unfamiliar database. Takes no parameters and answers instantly. trading_rt comes first: DEX trades, OHLC / volume bars, prices and supply for every trading chain over the last ~30 days — query it with execute_sql, browse it with list_tables, describe_table and search_columns. The per-chain databases (eth_api, bsc_api, matic_api, arbitrum_api, base_api, optimism_api, robinhood_api, arc_api, tron_api, solana, bitcoin, bitcoin_flow, ripple, ripple_flow, cardano, cardano_flow, altcoin, altcoin_flow - Litecoin, Dogecoin and Dash in one database, rows told apart by blockchain_id - bitcash, bitcash_flow for Bitcoin Cash, and stellar) hold transfers, calls, events, transactions and balances; browse them with chain_list_tables, chain_describe_table and chain_search_columns (pass the database name) and query each one with that chain's <chain>_transfers_raw_sql tool (xrp_, ada_, ltc_ / doge_ / dash_, bch_ and xlm_transfers_raw_sql for the ones above after bitcoin_flow). zcash and zcash_flow are queried with zec_transfers_raw_sql but the schema browser does not cover them: that tool's description lists their tables. stellar_flow is not browsable either - it starts in December 2023 and misses some ledgers, so query stellar instead. Address labels have no SQL access at all — use the label tools. Prefer a specialized tool whenever one answers the question: it already filters on the right keys and is far cheaper than hand-written SQL.
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  • Bulk ATLAS technique lookup — retrieve full records for up to 50 techniques in a single request instead of N separate atlas_technique_lookup calls. Designed as the natural follow-up to atlas_case_study_lookup, whose techniques_used array can be passed directly. Each item is the same shape as atlas_technique_lookup, including parent-tactics inheritance for sub-techniques (inherited_tactics=true flag) and per-item next_calls (D3FEND bridge when attack_reference_id present, sibling-technique search by tactic, parent lookup for sub-techniques). Free: 30/hr (1 per item), Pro: 500/hr. Returns {results [{technique_id, status (ok|not_found|invalid_format), technique, error}], total, successful, failed, partial, summary}.
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  • Get multiple Instagram posts by IDs (1-50 IDs per request). Returns results directly. Returns only found posts, omitting not-found IDs for flexibility. First searches database, then external API for missing/stale data in parallel. Use when you have multiple exact post IDs. NOT for search - use getInstagramPostsByKeywords. PERFORMANCE: Much more efficient than multiple single-ID calls. Batches database queries and parallelizes API calls. IMPORTANT: postIds must be in strong_id format (e.g., "3606450040306139062_4836333238") - use the full "id" value from other Instagram tools, NOT just the media_id. To find a post from an Instagram URL (e.g., instagram.com/p/ABC123/), extract the shortcode from the URL path and use getInstagramPostsByKeywords to search, or ask the user for the post ID. Optional fields parameter for performance: ["id", "caption", "likeCount"]. Returns: results array with id, caption, userId, username, createdAtDate, engagement metrics, count, dataSource. This is a safe, read-only tool for analyzing searchable information.
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  • Destroy a database and all its documents immediately - the teardown for finished work and the revocation kill switch for a leaked db URL. Irreversible: unlike expiry there is no restore window. Works on expired (frozen) databases too and consumes no quota. Call without confirm first: the response states the consequences; show them to the user and only retry with confirm="true" after their explicit approval. Afterwards remove the db URL from wherever you persisted it.
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  • Describe what's going wrong — your human's complaint, or a failure you notice in your own behavior — and get the matching techniques. Deterministic matching; if the description fits two problems it returns one clarifying question instead of guessing.
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  • Retrieve the complete markdown of one documentation article by the id returned from `search` (for example `en/claude-code/advanced-techniques/hooks-automation`). The text is returned in full; `metadata.gated` only reports whether the article sits behind the paywall on the web. An unknown id is an error — call `search` first.
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  • The operator's brand & PPC decision framework: margin spine (PPD + margin bands), product postures, campaign structure/bidding, harvesting/negation logic, guardrails and decision triggers. CALL THIS before analyzing an account or proposing ANY optimization (bids, budgets, negatives, harvest, campaigns, pricing) and follow it as the default operating model; pass section= (see toc) for a focused read.
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  • Find dated findings about code export, GitHub sync, backend connections and databases for Bubble, Lovable, Base44 and Replit. Use this to discover record IDs; get_finding retrieves one exact record. Other topics return no matches, not a product verdict.
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  • Look up a MITRE ATLAS technique — the AI/ML adversarial attack catalog. ATLAS catalogues TTPs targeting machine learning systems: prompt injection, model evasion, training data poisoning, model theft, etc. Roughly 80% of ATLAS techniques are AI/ML-specific (no ATT&CK bridge); 20% mirror an enterprise ATT&CK technique via attack_reference_id — use that to pivot to D3FEND defenses (d3fend_defense_for_attack) and CVE search. Sub-techniques inherit `tactics` from the parent (inherited_tactics=true flag) when ATLAS upstream leaves them empty. Use this tool when the user asks about AI/ML threats, LLM red-teaming, or adversarial ML; for multiple techniques in one call (e.g. drilling into a case study's techniques_used), prefer bulk_atlas_technique_lookup. Returns 404 when the id is not in the synced ATLAS catalog. Free: 30/hr, Pro: 500/hr. Returns {technique_id, name, description, tactics, inherited_tactics, maturity (demonstrated|feasible|realized), attack_reference_id, attack_reference_url, subtechnique_of, created_date, modified_date, next_calls}.
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  • Discovers and ranks URLs from a domain's XML sitemaps to find the most significant pages (homepages, product pages, recently updated content) before analyzing them. Supports URL-pattern filtering and automatically flags robots.txt-blocked and already-tested pages. Legal/policy boilerplate (privacy, terms, cookies, disclaimers, refunds) is flagged legalPage:true with a -25 significance penalty; use the legalPages filter to drop it (exclude) or isolate it for a policy-coverage audit (only). Parameters group into three jobs: discovery (url), ranking and paging (limit, sort), and filtering (include and exclude URL patterns, excludeDisallowed, excludeTested, excludeScheduled, legalPages).
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  • Discovers and ranks URLs from a domain's XML sitemaps to find the most significant pages (homepages, product pages, recently updated content) before analyzing them. Supports URL-pattern filtering and automatically flags robots.txt-blocked and already-tested pages. Legal/policy boilerplate (privacy, terms, cookies, disclaimers, refunds) is flagged legalPage:true with a -25 significance penalty; use the legalPages filter to drop it (exclude) or isolate it for a policy-coverage audit (only). Parameters group into three jobs: discovery (url), ranking and paging (limit, sort), and filtering (include and exclude URL patterns, excludeDisallowed, excludeTested, excludeScheduled, legalPages).
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