"jQuery" matching MCP tools:

• queryA

  Costory: Your Finops MCPA

  MINIMUM VALID CALL: { "queries": [{ "type": "cost", "name": "a", "metricId": "cost", "currency": "USD" }], "datePreset": "MTD", "aggBy": "Day" } Required per series: type (cost|metric|usage|formula|budget|externalMetric) and name. Put labels in alias. Unified query tool for cost data, custom metrics, usage metrics, external (live integration) metrics, period comparisons, formulas, and budgets. QUERY NAMING: set type and name (prefer short ids like a/b/c for formulas); put human labels in alias (e.g. "Cost by environment") — never in name. Example: { type: "cost", name: "a", alias: "Cost by environment", groupBy: "cos_environment", ... }. For costs: metricId (cost column, default "cost") and currency (default "USD"). Use costMetricId and currency from get when aligning with a budget. For custom business metrics: use [{ type: "metric", metricId: "..." }] — get IDs from list_metrics. For infra usage metrics (e.g. CPU hours, network bytes): use [{ type: "usage", metricId: "..." }] — call suggest_usage_metrics first to discover valid metricIds for your scope. For live external metrics (not saved as Costory metrics): use [{ type: "externalMetric", provider: "...", integrationId: "...", metricName: "...", aggregator: "SUM", groupByFields: [], conditions: "..." }] — discover provider, integrationId, and metricName via list_metrics with includeExternal: true and a specific search term. Tsuga: metricName is the provider metric name; groupByFields are provider metric attributes; conditions is an optional provider filter string. Datadog: same shape as Tsuga — metricName is the Datadog metric name (e.g. system.cpu.user), groupByFields are tag keys (e.g. host, service), conditions is an optional Datadog tag filter (e.g. env:prod). When query is set it is the Datadog metrics query string (pass-through); metricName / aggregator / conditions / groupByFields are ignored; .rollup is required and the interval must be ≥ 24h (daily / weekly / monthly or seconds ≥ 86400). Costory will not fill an empty weekly series. CloudWatch: set provider: "cloudwatch"; metricName is Namespace/MetricName (e.g. AWS/EC2/CPUUtilization); groupByFields are CloudWatch dimension names (e.g. InstanceId); conditions is an optional dimension filter. BigQuery: set provider: "bigquery"; metricName is the fully-qualified table id (project.dataset.table); dateColumn, metricColumn, and gapFillingMethod are required — pick dateColumn/metricColumn from list_metrics `schema` (first DATE / first NUMERIC) and default gapFillingMethod to FORWARD_FILL; groupByFields are string column names (not CEL). S3: set provider: "s3"; identical field shape to bigquery — metricName is the fully-qualified table id returned by list_metrics (a Costory-managed external table over the customer's mirrored Parquet); same schema-derived columns. Use externalMetric for exploration when no saved metric matches; prefer saved { type: "metric" } when one exists. PERIOD: prefer `datePreset` (same DatePreset enum as dashboards/reports, e.g. MTD, LAST_MONTH, TRAILING_30_DAYS, LAST_3_MONTHS, YTD) over hand-computed from/to whenever a preset matches — mutually exclusive with from/to. Response includes the resolved period dates. For comparison: add compare: {} (or compare: { from, to }) — omit compare dates to auto-derive the preceding period (preset-aware, e.g. LAST_MONTH → previous calendar month). For formulas: add { type: "formula", formula: "a / b" } referencing other queries by name. For budgets: use [{ type: "budget", budgetId: "..." }] — despite the field name, this must be the budget version ID (same value as budgetVersionId from get); search returns the parent budget id only, so call get with that id to obtain budgetVersionId before querying. Optional chartType on each query: BAR, LINE, AREA, WATERFALL, or TABLE (defaults to LINE). groupBy is the SPLIT dimension, filterCel is the SCOPE (CEL). Before guessing CEL field names, call search with type: ["dimensions"] — empty query lists all fields; a keyword narrows to matching values. Costory label dimensions use a cos_ prefix (e.g. cos_service_name). Unlabelled resources have null on label dimensions; use filterCel with == null / != null (not is_null or string "null"). Custom virtual dimensions: use immutable `bqName` from list/get VDIM tools as `groupBy` / `filterCel` (not display `name`). Poll `computeStatus` until `COMPLETED` after publish. Optional analyze.changePoint (true or { ignoreWeekends }) runs change-point detection once per query after a timeseries result (incompatible with compare). Optional limit (integer 1–1000): max groups/rows per series. Do NOT set limit unless you need a different cap — when omitted, results default to 100 groups. Set limit above 100 (e.g. 250 or 500) when the user asks for a long tail or full breakdown list. OPTIONAL: After receiving results, consider calling "list_events" for the same date range to correlate cost changes with events, and "suggest_actions" to present follow-up options to the user. EXAMPLES: • "What are my total costs this month?" → { queries: [{ type: "cost", name: "a", metricId: "cost", currency: "USD" }], datePreset: "MTD", aggBy: "Day" } • "Break down AWS costs by service over the last 90 days" → { queries: [{ type: "cost", name: "a", alias: "AWS by service", metricId: "cost", currency: "USD", groupBy: "cos_service_name", filterCel: "cos_provider in [\"AWS\"]" }], datePreset: "TRAILING_90_DAYS", aggBy: "Week" } • "Show costs for resources without an environment label" → { queries: [{ type: "cost", name: "a", metricId: "cost", currency: "USD", filterCel: "cos_environment == null" }], datePreset: "TRAILING_30_DAYS", aggBy: "Day" } • "How did our costs change vs last month?" → { queries: [{ type: "cost", name: "a", metricId: "cost", currency: "USD" }], datePreset: "LAST_MONTH", compare: {} } • "Show CPU hours alongside compute costs" (call suggest_usage_metrics first to get valid metricIds) → { queries: [{ type: "cost", name: "a", metricId: "cost", currency: "USD" }, { type: "usage", name: "b", metricId: "k8s_cpu_hours" }], datePreset: "TRAILING_30_DAYS", aggBy: "Week" } • "What is our cost per request?" → { queries: [{ type: "cost", name: "a", metricId: "cost", currency: "USD" }, { type: "metric", name: "b", metricId: "<metric-id>" }, { type: "formula", name: "c", formula: "a / b" }], datePreset: "TRAILING_30_DAYS" } • "Cost per request volume" (after list_metrics with includeExternal: true and search: "request") → { queries: [{ type: "cost", name: "a", metricId: "cost", currency: "USD" }, { type: "externalMetric", name: "b", provider: "tsuga", integrationId: "<integration-id>", metricName: "<metric-name>", aggregator: "SUM" }, { type: "formula", name: "c", formula: "a / b" }], datePreset: "TRAILING_30_DAYS", aggBy: "Week" } • "Cost per BigQuery revenue table" (after list_metrics with includeExternal: true and search: "revenue") → { queries: [{ type: "cost", name: "a", metricId: "cost", currency: "USD" }, { type: "externalMetric", name: "b", provider: "bigquery", integrationId: "<integration-id>", metricName: "my-project.analytics.revenue", dateColumn: "event_date", metricColumn: "amount", gapFillingMethod: "ZERO", aggregator: "SUM" }, { type: "formula", name: "c", formula: "a / b" }], datePreset: "TRAILING_30_DAYS", aggBy: "Week" } • "Cost per CPU usage from Datadog" (after list_metrics with includeExternal: true and search: "cpu") → { queries: [{ type: "cost", name: "a", metricId: "cost", currency: "USD" }, { type: "externalMetric", name: "b", provider: "datadog", integrationId: "<integration-id>", metricName: "system.cpu.user", aggregator: "AVG", groupByFields: ["host"] }, { type: "formula", name: "c", formula: "a / b" }], datePreset: "TRAILING_30_DAYS", aggBy: "Week" } • "Cost per EC2 CPU from CloudWatch" (after list_metrics with includeExternal: true and search: "CPUUtilization") → { queries: [{ type: "cost", name: "a", metricId: "cost", currency: "USD" }, { type: "externalMetric", name: "b", provider: "cloudwatch", integrationId: "<integration-id>", metricName: "AWS/EC2/CPUUtilization", aggregator: "AVG", groupByFields: ["InstanceId"] }, { type: "formula", name: "c", formula: "a / b" }], datePreset: "TRAILING_30_DAYS", aggBy: "Week" } • "Budget per calendar month" → { queries: [{ type: "budget", name: "a", budgetId: "<budgetVersionId>" }], datePreset: "LAST_3_MONTHS", aggBy: "Month" } (budgetVersionId from get, not the parent id from search) • "Budget month-to-date by day (cumulative within each month — which day did we reach the budget?)" → { queries: [{ type: "budget", name: "a", budgetId: "<budgetVersionId>", rollingAggregation: { aggregator: "SUM", window: { preset: "MONTH" } } }], datePreset: "MTD", aggBy: "Day" } • "Formula: month-to-date cost vs month-to-date budget (both rolling SUM per month, e.g. utilization a/b)" → { queries: [{ type: "cost", name: "a", metricId: "cost", currency: "USD", rollingAggregation: { aggregator: "SUM", window: { preset: "MONTH" } } }, { type: "budget", name: "b", budgetId: "<budgetVersionId>", rollingAggregation: { aggregator: "SUM", window: { preset: "MONTH" } } }, { type: "formula", name: "c", formula: "a / b" }], datePreset: "MTD", aggBy: "Day" } • Custom one-off range → { queries: [{ type: "cost", name: "a", metricId: "cost", currency: "USD" }], from: "2026-01-15", to: "2026-02-12", aggBy: "Day" }

  ConnectorOAuth

• check-packageA

  Jeevesus — DugganUSA Threat Intelligence MCPA

  Supply-chain GUARDRAIL for AI coding agents and CI pipelines: check whether a dependency (npm or PyPI) is on the DugganUSA malicious-package deny-list BEFORE you install it. This is the runtime defense against slopsquatting / HalluSquatting / hijacked-package attacks — an AI agent about to run `npm install` or `pip install`, or a CI pre-install hook, calls this FIRST and blocks on a hit. Returns a crisp, machine-actionable verdict: {ecosystem, package, version, malicious, verdict:"block"|"allow"|"review", reason, advice, source}. `malicious:true` = the exact package is on our OSV-curated deny-list (215k+ named-not-heuristic entries across npm + PyPI). `malicious:false` = not on our known-bad list — absence is NOT proof of safety, so still pin and review new deps. If a `version` is supplied and the entry is version-scoped, the check is version-aware; all-versions-malicious packages block on any version. Designed to be the easiest AI-supply-chain guardrail to wire in: one MCP tool call, no auth, in the agent's pre-install step. Same data is available for CI at /api/v1/stix-feed/packages.json. Examples: {"ecosystem":"npm","name":"cxp-jquery"} → malicious:true, verdict:block. {"ecosystem":"pypi","name":"requests"} → malicious:false, verdict:allow.

  ConnectorNo auth

• queryA

  Enhanciar — company brainA

  Ask Enhanciar a natural-language question grounded in the key's workspace. This is the high-level tool — use it for any "what does X do", "why did we choose Y", "where is Z handled" question. It runs the full retrieval + synthesis pipeline and returns the answer plus citations. Args: question: Natural-language question. model: Optional model id override (``gemini-2.5-flash``, ``gpt-4o``, ``claude-sonnet-4-5``, etc.). If omitted the saved default is used — the workspace's in a team workspace, the caller's own in a personal one. Returns ``{answer, sources, model}`` — ``sources`` is a list of ``{category, name, url}`` citations the LLM grounded its answer in. Surface them to the human so they can verify. When the workspace has nothing ingested at all you get ``{answer, empty_brain: true}`` and no sources: that is a statement about the workspace, not a failed search, so rephrasing the question will not change it.

  ConnectorNo auth

• queryA

  Foundry MCP code modeA

  Run a read-only script against the connected Foundry world. `code` is the body of an async function: call foundry.<domain>.<method>({ ... }) (see docs), use await, console.log, and return the value you want back (JSON, size-limited). Only read methods are bound; writes are not available here — use execute. Every call counts against the per-script limits shown in the docs index (calls, wall time, CPU time, result size); an oversized call result arrives as { __truncated: true, bytes, limit, preview }.

  ConnectorAPI key

• ontario_agent-pay-query-v2A

  Ontario ProtocolA

  Live x402 endpoint readiness check before payment. This x402 paid API verification service helps verify an x402 endpoint before an AI agent pays: probe one public paid API and inspect the HTTP 402 challenge, payTo address, price, Base USDC network and asset, manifest freshness, buyer budget, and spend policy. Returns ALLOW or DENY with reasons, readiness score, report ID, settlement metadata, and a settlement-backed SHA-256 evidence receipt. Run free can-pay and readiness checks first. Readiness evidence is not a safety guarantee. Agent payment guidance: run free can-pay and readiness checks first; pay only when policy allows base 0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913 and 0.002 USDC is inside the agent budget. [PAID: 0.002 USDC via x402 on Base. Two-step flow: call without payment to receive MCP PaymentRequired, then retry with params._meta['x402/payment'] containing the signed PaymentPayload. The legacy _x402_payment base64 argument is also supported. Sign only after explicit budget and policy approval.]

  ConnectorNo auth

• queryA

  OnePageCRMA

  Execute an OQL (OnePageCRM Query Language) query. Pass a JSON query object to read CRM data. Use describe() to discover entities and fields.

  ConnectorOAuth

• query-docsA

  ClearPolicyA

  Read or search ClearPolicy documentation pages via a sandboxed virtual filesystem (rg, cat, head, tree, ls, etc.). Prefer search-docs for conceptual questions; use this when you need exact page content, keyword/regex matches, or docs structure. Paths are documentation pages (e.g. /guides/reminders.mdx), not the customer organization.

  ConnectorOAuth

• queryA

  PhasioA

  Query the manufacturer's live data with an RSQL filter. Datasets: order (Orders and quotes share the same entity. The state field distinguishes QUOTE, ORDER, and DRAFT. Payment status is independent: a placed PO/invoice order can remain UNPAID until settlement. 'price' is the order total in the order's own 'currency'; 'localPrice' is the same total converted to the operator's home currency ('localCurrency'). Sum localPrice (not price) to compare revenue across orders in different currencies. 'source' is the sales channel: INBOUND = placed by the customer through the storefront (self-service, online); OUTBOUND = created and sent out by the manufacturer's team (a staff-built quote). Filter or group by source to split self-service vs staff-created orders.); partRevision (Part revisions (a versioned 3D part). 'designName' is the manufacturer's INTERNAL name for the part design — not what the customer sees; when a user names a part they usually mean the customer-facing requisition.name, so prefer that for matching user references. Geometry detail is via inspectPartRevision.); partSpecification (Part specifications: how a part revision is to be made (process, material, finish).); productionStep (A stage in production: a build group of parts undergoing one operation (e.g. 3D Print, Post-Process, Quality Control). Parts move from step to step as they are manufactured.); customerOrganisation (Customer organisations (the manufacturer's customers).); cart (Storefront shopping carts (status OPEN, CONVERTED to an order, or DELETED). Use for conversion analysis.); requisition (Requisitions: a part specification ordered on an order (the order line item; carries quantity and pricing). 'name' is the CUSTOMER-FACING part name — this is what customers and users call the line, so match it when someone refers to a part by name (filter name=="...", or name-contains via RSQL). It is distinct from the manufacturer's internal partRevision.designName; the same physical part can have a different customer-facing name here. pricePaid is the actual per-line revenue in the parent order's currency; localPricePaid is the same in the operator's home currency (sum this for cross-order revenue). quotedPrice is a snapshot taken at quote time and can be stale (use explainPrice to recompute).); workOrder (Work orders: production execution for a requisition (quantity to build, routing template). 'steps' is the ordered list of operations this work order will go through on the shop floor (its routing) — read it to know what will be done to build this order.); processPrices (Manufacturing processes and their pricing configuration. 'pricingAlgo' says how a process is priced: TS_EQUATION processes use a TypeScript pricing equation (activeTypescriptEquationId; read it with describePricingEquationApi(includeSource=true)); any other value is a legacy built-in algorithm with no equation to read. The row folds in the process's setup: boundingBox (max part size L x W x H), bulkQuantities (the quantity breaks shown for bulk pricing), materialVariables (the per-material variable names the equation reads), and counts of materials, post-processings, precision and infill options. isInternal processes are hidden from the storefront. A row with a customerOrganisationId is a customer-specific copy of a process.); materialPrices (A material's pricing configuration for one process (a process x material pairing). Carries the material (materialId/materialName), its density, and 'variables' — the material's TypeScript-equation variable values (operator-defined name=value pairs the pricing equation reads off the material). Use to see a material's rates without reverse-engineering them from quotes: filter by processPricesId and materialId (both from partSpecification). The 'variables' text isn't itself filterable — filter on materialId/processPricesId/density/isDefault instead. Rates are process-specific, so the same material can appear once per process.); postProcessing (Post-processing / finishing options the manufacturer offers (e.g. painting, polishing). 'type' says how it is priced: TS_EQUATION ones have their own TypeScript equation (activeTypescriptEquationId; read it with describePricingEquationApi(scope=POST_PROCESSING, ownerId, includeSource=true)); any other type is a legacy built-in formula with no equation to read. 'processes' lists the processes it is available on, 'operations' the shop-floor operations it adds, 'colors' its colour choices and 'incompatibleMaterials' the materials it cannot be applied to. Options sharing a mutuallyExclusiveGroup cannot be combined on one part.); typescriptEquation (TypeScript pricing equations (metadata only — describePricingEquationApi(includeSource=true) for the live source). 'scope' is PROCESS (processPricesId), POST_PROCESSING (postProcessingId) or ORDER (the operator's single order-level equation that adds whole-order line items; both ids null); 'isLive' tells whether it is the one currently used for quoting. Several draft equations can sit next to the live one; 'origin' is UI or MCP (written through save) and 'createdBy' the authoring user.); operation (Manufacturing operations (shop-floor stations) in 'sequence' order, e.g. 3D Print, Post-Process, Quality Control. Parts move operation to operation; batches moved at an operation are grouped into production steps (build groups). Column meanings: productionStepType is the station kind — BASE (a normal station), DOWNLOAD_PARTS_AS_GROUP (parts are downloaded as one build file), UPLOAD_THREED_NESTED (a nested build / bill of parts is uploaded), QUALITY_CONTROL (inspection; scrap is recorded here). viewType is the backlog's default view at this station: PART lists individual parts, BUILD lists build groups. buildConstraint says which parts may share one build group: NONE, MATERIAL (same material), MATERIAL_AND_COLOR, MATERIAL_AND_SHEET_THICKNESS. stepNamePrefix + stepNamingStrategy control how a new build group is named when a batch arrives: ALWAYS_RENAME (new name every time), RENAME_IF_BUILD_CHANGED (new name only when the build composition changed), INHERIT_FROM_PREVIOUS (keep the previous station's group name). allowOverproduction lets staff move more parts than the ordered balance. durationHours is the planning estimate for time spent at the station. isCompletedStatus marks the station whose exit means the part is finished. automations run when staff progress parts here (NOTIFY_ON_ORDER_COMPLETED). Referenced by productionStep.operationId and scrap.operationId.); batchMovement (Forward batch moves through production: each row is a batch of parts ADVANCING from one operation to the next (throughput). Scrap events are NOT here — see the scrap dataset for those. 'batchSize' is the quantity that moved; 'operationName' is the operation the batch left; 'toOperationName' is the one it moved to. Filter by createdAt for a time window or requisitionId/workOrderId for one job. For a SCRAP RATE by operation, aggregate sum(batchSize) here grouped by [operationName] (the parts that passed) and aggregate scrap the same way (the parts scrapped); rate = scrap / (scrap + moved) at each operation.); scrap (Scrap events: parts scrapped as they move through production. This is the floor-wide scrap log — query or aggregate it DIRECTLY for any scrap question; do not gather scrap by iterating requisitions or getProductionHistory. 'reason' is the free-text scrap cause; 'batchSize' is the quantity scrapped; 'operationName' is the operation the scrap happened at; filter by createdAt for a time window or requisitionId/workOrderId for one job. To find what causes the most scrap, aggregate sum(batchSize) grouped by reason (or operationName). For a scrap RATE you also need the parts that passed — aggregate the batchMovement dataset by operationName and divide.); material (The material catalogue (platform materials plus the manufacturer's own). Rates are NOT here — a material only has prices once it is paired with a process; query materialPrices (materialId==<id>) for those.); color (Colour options. Each colour belongs to one materialPrices row (a material on a process) or to one post-processing; 'kind' says which and the matching *Id column points at the parent.); jurisdiction (The platform's tax-jurisdiction catalogue: every code a taxJurisdiction can be created for, with its name and country. Platform reference data, identical for every manufacturer (not tenant data). Use it to find the isoCode for save(entity="taxJurisdiction"): filter by country (the Country enum name, e.g. GERMANY) and read the region names; DEFAULT and EXEMPT are the two special codes.); leadTime (Lead-time options offered at checkout. 'buffer' is the number of days added to the production estimate; the default one is pre-selected on the storefront and read by the pricing equation.); precisionPrices (Precision / tolerance options sold per process, each with a price adder. A row with a customerOrganisationId is a customer-specific override of the base option.); infill (Infill options per process (FDM-style density presets). 'infillValue' is the fill percentage; the default is pre-selected on the storefront. A row with a customerOrganisationId is a customer override.); taxJurisdiction (Tax setup per jurisdiction (country / region). 'components' lists the tax components applied (name and percentage) and 'totalPercentage' their sum. The DEFAULT jurisdiction is the fallback when a customer's address matches nothing; EXEMPT is used for tax-exempt customers.); taxComponent (Reusable tax components (e.g. VAT 19%) that jurisdictions combine. See taxJurisdiction.components for where each is applied.); paymentTerm (Payment terms offered to customers (e.g. Net 30). accountingSystemTermId links the term to the connected accounting system.); discount (Discounts: GENERIC (a code any customer can use), CUSTOMER (a code for one customer) or INSTANT (applied automatically). Active means endTime is in the future.); shippingBox (Shipping box sizes used to pack orders (dimensions in unitBasis).); shippingMethod (Shipping methods offered at checkout. shippingMode is FIXED_PRICE (flat price, optional weight tiers and a country list), CARRIER_ACCOUNT (live rates from the manufacturer's carrier account) or SELF_COLLECTION (pick-up). Tier and country detail is folded into the row.); routingTemplate (Routing templates: the ordered operations a work order goes through. 'steps' is the sequence of operation names. A template can be generic or bound to one partSpecification. When the storefront setting isApprovedRoutingTemplateRequired is on, only approved templates can be used.); kanbanColumn (Order-board (kanban) columns in display order. 'automations' lists what fires when an order enters the column (NOTIFY_CUSTOMER_OF_NEW_STATUS, SEND_INVOICE, SEND_ORDER_CONFIRMATION).); documentTemplate (Document templates (order confirmation, invoice, estimate, traveller sheets, labels) per language. Metadata only — use getDocumentTemplate(id) to read the HTML content.). Operators: == != =gt= =ge= =lt= =le= =in=(a,b) =out=(a,b); combine with ';' (AND) and ',' (OR). Each row is returned as 'field=value' pairs and always includes its id and foreign keys (the join keys); pass 'fields' to select specific columns (any field from describeQueryableFields). Call describeDataModel to see how datasets relate, and describeQueryableFields(entity) to learn a dataset's filterable fields.

  ConnectorAPI key

• queryA

  Washington State Open DataA

  Run a Socrata SoQL query against a Washington State Open Data dataset by resource_id (e.g. "qxh8-f4bd"). Filter with where/select/group/order (SoQL clauses, without the leading $) plus limit/offset. Returns matching rows as JSON.

  ConnectorNo auth

• queryA

  MydiseaseA

  Search MyDisease.info for diseases by free-text name or fielded query. Returns matching hits, each keyed by a MONDO disease id (e.g. "MONDO:0015967") with the best-matching ontology and annotation keys. Use this to resolve a disease name to canonical ontology ids before calling the "disease" tool. Free text like "diabetes" or "asthma" works; fielded queries like "mondo.label:asthma" or "disgenet.xrefs.disease_name:..." narrow the search.

  ConnectorNo auth

• queryA

  Data DelawareA

  Run a Socrata SoQL query against a Delaware Open Data dataset by resource_id (e.g. "5zy2-grhr"). Filter with where/select/group/order (SoQL clauses, without the leading $) plus limit/offset. Returns matching rows as JSON.

  ConnectorNo auth

• queryA

  Data PaA

  Run a Socrata SoQL query against a Pennsylvania Open Data dataset by resource_id (e.g. "mcba-yywm"). Filter with where/select/group/order (SoQL clauses, without the leading $) plus limit/offset. Returns matching rows as JSON.

  ConnectorNo auth

• queryA

  Data VaA

  Run a Socrata SoQL query against a Virginia Open Data dataset by resource_id (e.g. "rdpw-mtbs"). Filter with where/select/group/order (SoQL clauses, without the leading $) plus limit/offset. Returns matching rows as JSON.

  ConnectorNo auth

• query-vybe-apiA

  Solana MCP by VybeA

  Runs a read-only GET request against a documented /v4 path on the Vybe Solana API (see https://docs.vybenetwork.com) and returns live Solana data: token prices, holders, liquidity and candles; wallet balances, PnL, counterparties and DeFi positions; markets, trades, transfers, top traders and labeled accounts. Use list-endpoints or search-endpoints to find a path and get-endpoint to check its parameters first. This tool cannot create, modify, or delete anything.

  ConnectorNo auth

• query-vybe-api-batchA

  Solana MCP by VybeA

  Reads Solana wallet data for many addresses in one call from the Vybe Solana API (see https://docs.vybenetwork.com). These endpoints use a POST body only to carry the list of wallet addresses; they do not create, modify, or delete any data. Use query-vybe-api for single-wallet and all other reads.

  ConnectorNo auth

• queryA

  Maryland Open DataA

  Run a Socrata SoQL query against a Maryland Open Data dataset by resource_id (e.g. "2ir4-626w"). Filter with where/select/group/order (SoQL clauses, without the leading $) plus limit/offset. Returns matching rows as JSON.

  ConnectorNo auth

• queryA

  Data CookcountyA

  Run a Socrata SoQL query against a Cook County Open Data dataset by resource_id (e.g. "cjeq-bs86"). Filter with where/select/group/order (SoQL clauses, without the leading $) plus limit/offset. Returns matching rows as JSON.

  ConnectorNo auth

• queryA

  MychemA

  Search MyChem.info for drugs / chemical compounds. Accepts a plain drug name ("aspirin"), an InChIKey, or a fielded query (e.g. "chembl.pref_name:aspirin", "drugbank.name:Acetylsalicylic acid"). Returns aggregated hits with cross-references to ChEMBL, DrugBank, PubChem, ChEBI, DrugCentral, etc. Use this to resolve a drug name into structured identifiers.

  ConnectorNo auth

• queryA

  Data PiercecountyA

  Run a Socrata SoQL query against a Pierce County Open Data dataset by resource_id (e.g. "hmbh-c3hw"). Filter with where/select/group/order (SoQL clauses, without the leading $) plus limit/offset. Returns matching rows as JSON.

  ConnectorNo auth

• queryA

  Data FccA

  Run a Socrata SoQL query against a FCC Open Data dataset by resource_id (e.g. "3xyp-aqkj"). Filter with where/select/group/order (SoQL clauses, without the leading $) plus limit/offset. Returns matching rows as JSON.

  ConnectorNo auth

• queryA

  Data MichiganA

  Run a Socrata SoQL query against a Michigan Open Data dataset by resource_id (e.g. "fbey-tu9a"). Filter with where/select/group/order (SoQL clauses, without the leading $) plus limit/offset. Returns matching rows as JSON.

  ConnectorNo auth