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135,112 tools. Last updated 2026-05-25 21:45

"Understanding and Writing Unit Tests" matching MCP tools:

  • Get Lenny Zeltser's cybersecurity-writing rating sheet(s) so your AI can apply the rubric. Returns the structured rubric (groups, items, scoring bands) WITHOUT computing a score. Use `rating_score_writing` if you also want a numeric score, gap analysis, or rubric-anchored feedback. This server never requests your draft and instructs your AI to keep it local—rating sheets and scoring instructions flow to your AI.
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  • 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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  • Fetch full metadata and column schema for a Socrata dataset by ID. Returns field names, data types, descriptions, row count, and licensing. Always call this before writing a socrata_query_dataset — the column types determine correct WHERE clause syntax: Number columns accept bare literals (year=2023) while Text columns require single-quoted strings (year='2023').
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  • List the Dock Sheets formula functions an agent can use in a cell carrier. Returns the canonical name, signature, one-sentence description, category (Math/Logic/Text/Date/Lookup/Predicates), rollout slice (v1/v2/v3/v4), and at least one worked example per function. Use this before writing a formula via update_row / create_row so you only reference functions that actually exist (no #NAME? errors). Also returns the alias map (e.g. CONCAT → CONCATENATE) so you can pick the canonical name even when writing the alias the UI accepts. Optional filters: `category` narrows to one category, `slice` narrows to one rollout slice, `name` substring-matches names + descriptions + signatures. Public, no auth, no rate limit beyond global.
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  • Get native ETH and ERC20 token balances for a wallet address. Reads directly from chain via RPC multicall. Use before write_account_add_liquidity or write_account_deposit to verify the wallet has sufficient tokens. Returns both raw balance (smallest unit/wei) and formatted (human-readable) per token.
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  • Quote the minimum unit price for a buy. Returns `{ minPrice }` (SUN per resource unit) from GraphQL `market.estimateMinPrice` for the given `resourceType`, `buyAmount`, and `durationSec`. Optional `address` scopes context when the API supports it. No login required; an optional session forwards auth like `tronsave_list_order_books`. Read-only and idempotent. Pair with `tronsave_estimate_buy_resource` for full buy quotes and `tronsave_list_order_books` for depth buckets.
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Matching MCP Servers

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  • Flaky test detection, root cause analysis, and fix suggestions for development teams.

  • USGS commodity benchmarks, attested field run logs, and mining/geologic district data for AI agents. Nine data endpoints gated by x402 ($0.10 USDC on Base). Tools: get_commodity_benchmark (gold, silver, copper, and 17 more critical minerals), get_ultrasound_run_data (on-chain EAS-attested gravity-separation field runs), district.history (MRDS-sourced deposit and assay history by country/state/district), and ask_sales_agent. No API keys — pay per call in USDC.

  • Search Hansard for parliamentary debates, questions, and speeches. Returns contributions from MPs and Lords including date, party, debate title, and text (capped at 3000 chars per contribution). Useful for understanding legislative intent or political context.
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  • Quote the minimum unit price for a buy. Returns `{ minPrice }` (SUN per resource unit) from GraphQL `market.estimateMinPrice` for the given `resourceType`, `buyAmount`, and `durationSec`. Optional `address` scopes context when the API supports it. No login required; an optional session forwards auth like `tronsave_list_order_books`. Read-only and idempotent. Pair with `tronsave_estimate_buy_resource` for full buy quotes and `tronsave_list_order_books` for depth buckets.
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  • Get summary statistics of the Klever VM knowledge base. Returns total entry count, counts broken down by context type (code_example, best_practice, security_tip, etc.), and a sample entry title for each type. Useful for understanding what knowledge is available before querying.
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  • 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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  • Get Lenny Zeltser's scoring playbook so your AI can score a draft locally against a cybersecurity-writing rating sheet. THIS IS THE ONLY TOOL THAT PRODUCES NUMERIC SCORES — the writing-coach tools (`get_security_writing_guidelines`, `ir_*`, `product_*`) never score. Returns the rubric plus step-by-step instructions for applying it. This server never requests your draft and instructs your AI to keep it local—rating sheets and scoring instructions flow to your AI.
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  • 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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  • Load Lenny Zeltser's complete cybersecurity-writing rating toolkit: all 7 sheets, scoring policy, scoring playbook, and cross-references to the writing guidelines. This server never requests your draft and instructs your AI to keep it local—rating sheets and scoring instructions flow to your AI.
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  • Resolve the storage mode for V1 ("user maintains the flow") API tests on this app. ═══════════════════════════════════════════════════════════════════ **MUST BE YOUR FIRST MCP CALL** for ANY of these dev verbs/intents: ═══════════════════════════════════════════════════════════════════ * "run the sandbox tests" / "run the API tests" / "test sandbox" / "run keploy tests" * "record the sandbox" / "rerecord" / "refresh the mocks" / "capture mocks" * "replay the sandbox" / "replay the tests" / "show me the report" / "what failed in the last run" * "generate keploy tests" / "add a keploy test for <endpoint>" * "set up keploy in this repo" / "onboard this service to keploy" * any other reference to keploy/api-tests/, sandbox tests, integration tests, mocks, suites REASON: this is the gate that determines whether the app is on the V1 (repo-mode) code path or the legacy cloud-mode code path. **The two paths use entirely different MCP tool surfaces**: ┌───────────────────────┬─────────────────────────────────────────────────────────┐ │ Storage mode │ Tools to use │ ├───────────────────────┼─────────────────────────────────────────────────────────┤ │ "repo" │ devloop_* tools only. NO cloud-mode tools. │ │ │ (record_sandbox_test, replay_sandbox_test, │ │ │ replay_test_suite, create_test_suite, list_branches, │ │ │ get_app_testing_context, listTestSuites etc. will │ │ │ REFUSE with a redirect to the V1 surface.) │ ├───────────────────────┼─────────────────────────────────────────────────────────┤ │ "cloud" or "" (unset) │ Cloud-mode tools (record_sandbox_test, │ │ │ replay_sandbox_test, replay_test_suite, │ │ │ create_test_suite, list_branches, get_app_testing_ │ │ │ context, listTestSuites, etc.). devloop_* tools may │ │ │ also be called for the V1 cloud-mode path. │ └───────────────────────┴─────────────────────────────────────────────────────────┘ DO NOT SKIP THIS. If you reach for cloud-mode tools first (replay_sandbox_test, list_branches, listTestSuites, etc.) without calling devloop_resolve_storage, you WILL misroute repo-mode apps and tell the dev to "upload local tests as suites and record into the cloud" — the EXACT regression that prompted these MCP-side guardrails. The cloud-mode tools server-side gate on devloop_storage_mode == "repo" and will refuse the call with a redirect message; devloop_resolve_ storage front-runs that refusal cleanly. Resolution order: 1. If app.devloop_storage_mode is set → return {mode, source: "persisted"}; do NOT re-ask. 2. Else if the dev's repo (app_dir) already contains keploy/api-tests/ → ATEMPT to infer repo mode. This tool returns source="asked" with a hint asking you to check the dev's filesystem; if you confirm keploy/api-tests/ exists, call devloop_set_storage_mode({app_id, mode:"repo", reason:"inferred_local_tests_exist"}) and proceed silently. 3. Else → return {source: "asked"} with the trade-off text in `message`; surface that to the dev, get yes/no, persist via devloop_set_storage_mode. The AI is responsible for inspecting the repo (this MCP server does not have filesystem access). Use your native filesystem tools (read/grep) to check whether keploy/api-tests/ exists under app_dir. APP RESOLUTION — the dev should NEVER have to type an app_id. Pass EITHER: * app_id (UUID) — exact, fast path. Use this once you've resolved it earlier in the conversation. * app_name_hint — a case-insensitive substring of the app name (typically the cwd basename). The tool calls listApps(q=hint) and resolves to a unique match. If neither is set, the tool errors with the candidate list so you can ask the dev. If app_name_hint matches multiple apps, the error names them and asks you to disambiguate. If no app matches, you propose creating one (call createApp) BEFORE re-running this tool.
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  • Persist the V1 storage mode on an app. Call this AFTER devloop_resolve_storage returned source="asked" (the dev gave you a yes/no) or source="inferred" (you confirmed keploy/api-tests/ exists on disk). Switching repo→cloud when local tests exist warns the dev that the existing local tests will be orphaned (Keploy will start sourcing tests from MongoDB; the keploy/api-tests/ files are no longer the source of truth). Surface the warning before calling this tool with mode="cloud" against a repo that has local tests.
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  • Fetch metadata for a Eurostat dataset: dimensions with valid values, time range, observation count, and last-update date. Call this before eurostat_query_dataset to discover what dimension codes are valid (unit, na_item, geo, etc.). Returns up to 10 sample values per dimension for orientation; use eurostat_get_dimension_values to list the full set for large dimensions.
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  • Fetches complete metadata for a single World Bank indicator by its ID: name, description, source dataset, source organization, unit, and thematic topics. Use worldbank_search_indicators to discover indicator IDs if you only know the concept.
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  • Validate formula syntax with the WorkPaper parser before writing it to a cell. This checks syntax only; use set_cell_contents plus readback to evaluate.
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  • Search for datasets across all Socrata-powered government open-data portals, or scope to one portal with the domain parameter. Returns dataset IDs, names, abbreviated column lists, domains, and update timestamps. Use socrata_get_dataset to fetch the full typed column schema before writing queries — columnNames here are preview-only and lack type information.
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  • Analyze domain email authentication posture: SPF, DMARC, DKIM with numeric score and findings. Dual-use: red-team (spoofing feasibility) + blue-team (posture audit). Score 0-100, grades A+-F. DKIM probing tests common selectors + recent dates; custom selectors must be supplied. Passive DNS-only; no SMTP probe. Free: 30/hr, Pro: 500/hr.
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