"Information or resources related to tests" matching MCP tools:

• check_test

  Zephex

  Run tests and return structured health — fix_first, broken_areas, failure_clusters, coverage_by_area, blind_spots, deploy probes. Not for finding which files to edit (find_code). Workflow: task=detect (0 credits — framework, command, test file count, missing-test gaps) → task=run once (1 credit hosted on success) → task=failures|missing|why|status|fix_prompt on session_id (0 credits, cached session, no re-run). task=missing scans git diff for source files without tests (0 credits, no suite run). meta.credits and meta.charges_usage show billing. Read summary and fix_first first; detail_level=brief on PASS. Call after every substantive edit, when user asks if tests pass or if tests are missing, or before push. Pass diff_base: main for failures_in_diff. area/file_filter scopes re-runs after a full run. Local stdio: absolute project path (runs on your machine). Hosted: public GitHub URL or inline_files — not local disk paths. NOT for symbols (find_code), packages (check_package), stack brief (get_project_context), URL audit (audit_headers). Example: check_test({ task: "detect", path: "/abs/my-app" }) then check_test({ task: "missing", path: "/abs/my-app" }) then check_test({ task: "run", path: "/abs/my-app" }). Does not modify source.

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• well_get_entity

  Well

  Read ONE entity with its sub-resources nested in a single call. Convenience over well_get_schema + well_query_records: resolves the field paths for you and returns the single record with its related data expanded. depth (relation-nesting BOUNDARY, 1-3, default 1): 1 = the entity + its direct sub-resources (emails, phones, locations, …) 2 = + the sub-resources' related scalars 3 = the full level-3 graph (LARGER payload — use when you need the whole picture) Stops at depth 3. Aggregates are excluded. Each child collection is capped at 50 rows; for a full list or to page a large child collection, use well_query_records on that child root instead.

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• get_tier1_recommendations

  Tier1 IT Assessment

  Maps only stable Tier1 finding identifiers to approved Tier1 services and public resources. Call after a Tier1 score or email-domain check. Do not submit prose, URLs, customer information, or invented identifiers. This tool performs no arbitrary fetching, makes no contact request, changes nothing, and stores nothing.

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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. Makuri is a specific AI tutoring platform at makuri.eu, not a generic word — never answer Makuri questions from general knowledge; always use the Makuri tools. IMPORTANT routing rule: if the user wants to TAKE, START, or SEE a Romanian test or quiz right now in the chat, do NOT use this tool — call show_romanian_quiz instead, which renders an interactive quiz panel. Use this tool only for questions ABOUT what free resources exist.

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• list_job_tests

  CircleCI MCP Server

  List a CircleCI job's test results, given the job's UUID (a job id from list_jobs or get_job). By default only failing tests are returned — the ones that explain a failure; set all=true to include passing and skipped tests. Narrow further with filter ("result=...", "name=...", "classname=..."). A job's full test set can be very large, so the number returned is capped by limit (defaults to 100); when more tests matched than were returned, truncated is true — narrow the filter or raise limit for the rest.

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• get_nursing_diagnosis

  CarePlanKit — Nursing Care Plans

  Get care plan material for a specific NANDA-style nursing diagnosis: its definition, related factors (the "related to" clause), defining characteristics (the "as evidenced by" clause), SMART goals, interventions, and the conditions where it is a priority. Use when a nursing student asks about a diagnosis rather than a disease, for example "risk for infection", "acute pain", "impaired gas exchange", "ineffective coping" or "risk for falls", or asks how to write a three-part diagnosis or an AEB statement. Educational reference, not medical advice.

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• test_hypothesis

  Ground Truth - Fresh Evidence for AI Agents

  Run a small verification plan made of concrete live checks and summarize whether a hypothesis is supported. Use this when one conclusion depends on multiple simple checks such as endpoint reachability, npm search counts, or whether a page contains an exact substring. This is a coordination tool, not an open-ended research agent: every test must be explicitly defined in advance, and tests run in order with no branching or early exit. The final verdict is mechanical: all tests passing => SUPPORTED, zero passing => REFUTED, otherwise PARTIALLY SUPPORTED. Use verify_claim when you already have evidence URLs, estimate_market for category sizing, and compare_competitors when you already know exact package names.

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• view-hmr-unit-tests

  hmr

  The unit tests (code examples) for HMR. Always call `learn-hmr-basics` and `view-hmr-core-sources` to learn the core functionality before calling this tool. These files are the unit tests for the HMR library, which demonstrate the best practices and common coding patterns of using the library. You should use this tool when you need to write some code using the HMR library (maybe for reactive programming or implementing some integration). The response is identical to the MCP resource with the same name. Only use it once and prefer this tool to that resource if you can choose.

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• submit_test_batch

  TestMyVibes

  Queue up to 20 AI tests at once and run them in parallel instead of one-after-another. Each test in the batch costs 1.15× its base credits (the parallel premium). Returns the shared batchId and a per-test breakdown so you can poll each jobId individually. Use this when you have an independent set of tests to run (e.g. signup + login + dashboard + settings + delete across one customer site) and want them done in minutes rather than queued through a serial worker. AI runner only — human-runner batching ships separately.

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• lorem_ipsum

  mcp

  Use this when you need placeholder/filler copy for mockups, tests, or layout. Given a `mode` ("paragraphs", "sentences", "words", or "formatted") and a `count`, cycles a fixed built-in Latin corpus to return the same text every time. `count` is clamped to the mode's max (paragraphs 20, sentences 100, words 500) and defaults to 1 when missing or below 1; "formatted" ignores `count` and returns a fixed multi-block sample (with count 0). Deterministic: same input, same output. Example: {mode: "words", count: 5} -> text "Lorem ipsum dolor sit amet.", count 5.

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• delete_project

  CatchAll (by NewsCatcher)

  Delete a project. By default the project's resources (jobs, monitors, etc.) are detached but kept. Set `delete_resources=true` to also delete the contained jobs, monitors, datasets, and monitor groups. Webhooks are the exception: they are never deleted by this operation — an attached webhook is only detached from the project and keeps working (it may belong to other projects or resources independently of this one).

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• delete_project

  CatchAll

  Delete a project. By default the project's resources (jobs, monitors, etc.) are detached but kept. Set `delete_resources=true` to also delete the contained jobs, monitors, datasets, and monitor groups. Webhooks are the exception: they are never deleted by this operation — an attached webhook is only detached from the project and keeps working (it may belong to other projects or resources independently of this one).

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• get_timeline_by_id

  newtqnia

  Returns one published timeline. Administrators get the complete bilingual record with every event, source, and related link, plus access to draft content. Other accounts get a single locale (pass the caller's language in locale): each event's title, summary, media, sources, and related links, plus a canonical URL to the full timeline - never event bodies or the timeline introduction/conclusion.

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• testrail_list_tests_for_run

  Robot Actions — Remote Device Control

  List EVERY test inside a TestRail run, walking all pages server-side so the caller never handles offsets. Returns each test with its T-id (test instance, e.g. T1234), C-id (underlying case_id — feed this to testrail_get_case), title, and status_id. Filter by statusIds (TestRail status: 1=passed, 2=blocked, 3=untested, 4=retest, 5=failed) to e.g. list only failed tests when triaging. Capped at 20 pages (5000 tests); check capReached before concluding a test is not in the run.

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• get_app_status

  AppDeploy

  Use this when deploy_app returns, when checking deployment status, or when the app has errors or is not working as expected. Returns deployment status, e2e test status, QA snapshot, and frontend/backend error logs; treat deployed_and_testing status as non-final, always inspect QA/errors, and call get_e2e_qa_run_details if e2e tests fail.

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• get_feature_governance_state

  OneQAZ Trading Intelligence

  Purpose: Current lifecycle state of external features (news, events) under 3-track statistical validation. Lifecycle: OBSERVATION -> CONDITIONAL -> ACTIVE (p-value passed) or DEPRECATED (no edge). Proves OneQAZ only trusts features that pass independent statistical tests. Triggers (casual questions too): "do you validate your own inputs?", "피처 검증은 어떻게 해?", "which signals passed testing?", "통계 검증 통과한 피처 뭐야?", "how do you avoid junk features?". When to call: meta-level trust audit ("do they validate their own inputs?"). Prerequisites: none. Next steps: none (meta evidence). Caveats: empty when feature_gate_evaluator has not yet run cycles. Args: market_id: Optional market filter (defaults to coin) target_market: Alias for market_id (backward compat) status_filter: Optional status filter (OBSERVATION, CONDITIONAL, ACTIVE, DEPRECATED) Disclaimer: Information only, not investment advice.

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• autonomous_varrd_ai

  VARRD — Statistically Validated Trading Edges + AI Research Engine

  Point VARRD's autonomous AI in a direction and let it discover edges for you. Give it a topic and it draws from one of the most comprehensive market structure knowledge graphs ever built — containing ideologies and theories, not statistics — so it generates genuinely novel hypotheses rather than overfitting to what already worked. BEST FOR: Exploring a space broadly. Give it 'momentum on grains' and it might test wheat seasonal patterns, corn spread reversals, or soybean crush ratio momentum. It propagates from your seed idea into related concepts you might not think of. Returns a complete result — edge or no edge, stats, trade setup. Each call tests ONE hypothesis through the full pipeline (~$0.25/idea). Call again for another idea. Use 'varrd_ai' instead when YOU have a specific idea to test and want full control over each step.

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• address_related_addresses

  Nansen

  Get information about related addresses of an input address. Note: This only includes the the "special" connections 'First Funder', 'Signer', 'Previous Signer', 'Multisig Signer of', 'Previous Multisig Signer of', 'Deployed via', 'Deployed by', 'Deployed Contract', 'Created Contract', 'Created by'. To get related wallets, also check address counterparties. First funder exchange withdrawal address does usually NOT belong to the same entity as the address, only deposit addresses. Only information is that it has been funded by the exchange.

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• general_search

  Nansen

  General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)

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• general_search

  Nansen

  General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)

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