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307,679 tools. Last updated 2026-07-18 18:18

"author:darrylsarkisian-debug" matching MCP tools:

  • Core dossier check: Retrieve and parse a domain's SPF record, decomposing it into mechanisms and qualifiers. Use to verify email sender policy, debug delivery failures, or check the 10-lookup limit; pair with dossier_dmarc for full email-auth coverage, or use dns_lookup with type=TXT for the raw record only. Fetches TXT records via Cloudflare DoH (1.1.1.1), 5 s timeout, locates the v=spf1 record and parses all mechanisms. Returns a CheckResult: on success, {status:"ok", raw, mechanisms:[{type, value, qualifier},...], lookupCount}; on failure, {status:"error", reason}.
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  • PREFER THIS over guessing tool names when picking from this server. Searches Flow Studio MCP tools by keyword, skill bundle, or explicit selector and returns full JSON schemas for matched tools so they can be called immediately. Call this whenever the user request maps to functionality you are not 100% sure about, OR when you want to load a whole skill bundle (build-flow, debug-flow, monitor-flow, discover, governance) at once. Query forms: (1) "skill:<name>" — fetch the full bundle (use list_skills first to see options); (2) "select:name1,name2" — fetch exact tools by name; (3) free-text keywords like "cancel run" or "trigger url" — ranked match against tool name + description. Non-billable.
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  • Semantic search — match by meaning, not exact words. Uses vector similarity (cosine distance) over `text_pali` embedded with a multilingual MiniLM model. 🤔 **In most cases you should use `search_hybrid` instead** — it combines this semantic search with keyword search and ranks better. Use this tool only when you need: - Pure semantic results (no keyword influence) - Fine-grained `threshold` tuning (hybrid uses RRF which is harder to tune) - To debug what semantic alone picks up vs keyword ⚠️ Known limitations: - The index is **Pāli only** (English/Thai queries pass through the multilingual embedding but the model isn't tuned on Pāli) - English queries usually embed better than Thai (model is EN-primary) - For specific Pāli terms (`appamāda`, `dukkha`), exact match is better — use `search_by_keyword` instead - Pāli stock phrases recur in many suttas → similarity scores cluster; read the top 10, don't trust rank 1 alone
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  • Returns the canonical guide for using TMV from a coding-agent context. Covers the fix-test-retest loop, how to write a good test prompt, how to read the actionTrail / consoleErrors / failedRequests outputs, and common gotchas. Call this first if you're a new agent on a project — it'll save you a debug session. The same content is served at https://testmyvibes.com/docs/coding-agents.
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  • MCP debug tool: echoes the `message` argument back to the client. Useful as a smoke test for the MCP gateway. Use only for MCP debugging. Do not use under normal circumstances.
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  • ## ⚠️ MANDATORY TOOL FOR ALL I18N WORK ⚠️ THIS IS NOT OPTIONAL. This tool is REQUIRED for any internationalization, localization, or multi-language implementation. ## When to Use (MANDATORY) **ALWAYS use this tool when the user says ANY of these phrases:** - "set up i18n" - "add internationalization" - "implement localization" - "support multiple languages" - "add translations" - "make my app multilingual" - "add French/Spanish/etc support" - "implement i18n" - "configure internationalization" - "add locale support" - ANY request about supporting multiple languages **Recognition Pattern:** ``` User message contains: [i18n, internationalization, localization, multilingual, translations, locale, multiple languages] → YOU MUST call this tool as your FIRST ACTION → DO NOT explore the codebase first → DO NOT call other tools first → DO NOT plan the implementation first → IMMEDIATELY call: i18n_checklist(step_number=1, done=false) ``` ## Why This is Mandatory Without this tool, you will: ❌ Miss critical integration points (80% failure rate) ❌ Implement steps out of order (causes cascade failures) ❌ Use patterns that don't work for the framework ❌ Create code that compiles but doesn't function ❌ Waste hours debugging preventable issues This tool is like Anthropic's "think" tool - it forces structured reasoning and prevents catastrophic mistakes. ## The Forcing Function You CANNOT proceed to step N+1 without completing step N. You CANNOT mark a step complete without providing evidence. You CANNOT skip the build check for steps 2-13. This is by design. The tool prevents you from breaking the implementation. ## How It Works This tool gives you ONE step at a time: 1. Shows exactly what to implement 2. Tells you which docs to fetch 3. Waits for concrete evidence 4. Validates your build passes 5. Unlocks the next step only when ready You don't need to understand all 13 steps upfront. Just follow each step as it's given. ## FIRST CALL (Start Here) When user requests i18n, your IMMEDIATE response must be: ``` i18n_checklist(step_number=1, done=false) ``` This returns Step 1's requirements. That's all you need to start. ## Workflow Pattern For each of the 13 steps, make TWO calls: **CALL 1 - Get Instructions:** ``` i18n_checklist(step_number=N, done=false) → Tool returns: Requirements, which docs to fetch, what to implement ``` **[You implement the requirements using other tools]** **CALL 2 - Submit Completion:** ``` i18n_checklist( step_number=N, done=true, evidence=[ { file_path: "src/middleware.ts", code_snippet: "export function middleware(request) { ... }", explanation: "Implemented locale resolution from request URL" }, // ... more evidence for each requirement ], build_passing=true // required for steps 2-13 ) → Tool returns: Confirmation + next step's requirements ``` Repeat until all 13 steps complete. ## Parameters - **step_number**: Integer 1-13 (must proceed sequentially) - **done**: Boolean - false to view requirements, true to submit completion - **evidence**: Array of objects (REQUIRED when done=true) - file_path: Where you made the change - code_snippet: The actual code (5-20 lines) - explanation: How it satisfies the requirement - **build_passing**: Boolean (REQUIRED when done=true for steps 2-13) ## Decision Tree ``` User mentions i18n/internationalization/localization? │ ├─ YES → Call this tool IMMEDIATELY with step_number=1, done=false │ DO NOT do anything else first │ └─ NO → Use other tools as appropriate Currently in middle of i18n implementation? │ ├─ Completed step N, ready for N+1 → Call with step_number=N+1, done=false ├─ Working on step N, just finished → Call with step_number=N, done=true, evidence=[...] └─ Not sure which step → Call with step_number=1, done=false to restart ``` ## Example: Correct AI Behavior ``` User: "I need to add internationalization to my Next.js app" AI: Let me start by using the i18n implementation checklist. [calls i18n_checklist(step_number=1, done=false)] The checklist shows I need to first detect your project context. Let me do that now... ``` ## Example: Incorrect AI Behavior (DON'T DO THIS) ``` User: "I need to add internationalization to my Next.js app" AI: Let me explore your codebase first to understand your setup. ❌ WRONG - should call checklist tool first AI: I'll create a middleware file for locale detection... ❌ WRONG - should call checklist tool to know what to do AI: Based on my knowledge, here's how to set up i18n... ❌ WRONG - should use checklist tool to coordinate implementation ``` ## Why Sequential Steps Matter The 13 steps have strict dependencies: - Can't implement routing (step 3) without locale resolution (step 2) - Can't load translations (step 6) without data source (step 5) - Can't use translation API (step 8) without context (step 7) - Can't add UI switcher (step 12) without switching logic (step 11) Skipping or reordering steps creates broken implementations that are hard to debug. ## Common Mistakes to Avoid ❌ "Let me plan out the implementation first" → NO, call the tool ❌ "Let me check your project structure" → NO, call the tool (it will tell you when) ❌ "I'll implement based on my knowledge" → NO, call the tool (it fetches current docs) ❌ "I'll skip step X since it seems optional" → NO, all steps are mandatory ❌ "I've done this before, I know what to do" → NO, frameworks differ, use the tool ## The Tool Coordinates Everything This tool tells you when to: - Call get_project_context (step 1) - Call get_framework_docs (steps 2-13) - Call get_i18n_library_docs (steps 7-10) - Implement specific code (every step) - Run builds (steps 2-13) - Move to the next step (after evidence validation) Don't try to orchestrate this yourself. Let the tool guide you. ## Summary: Your First Action When user requests i18n support: 1. Recognize the trigger words (internationalization, localization, i18n, etc) 2. IMMEDIATELY call: i18n_checklist(step_number=1, done=false) 3. Follow the instructions it returns 4. That's it - the tool handles the rest This is not a suggestion. This is MANDATORY for all i18n work.
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  • Schedule and manage Google Calendar events directly from your workspace. Check availability, view…

  • Debug webhooks from your AI agent: inspect and replay captured webhooks on localhost.

  • Bounded, permission-gated shared context store for authenticated aX workspace state. The tool reads and writes only first-party aX context/catalog state. It does not call external systems, deploy, rotate credentials, or perform open-world destructive operations. delete/decline/terminate remove only ephemeral TTL-bound working copies and are gated behind a can_delete permission; durable vault copies and governed catalog entries cannot be deleted through this tool. Shared context has three tiers: ephemeral, vault, and governed catalog. Space is always implied from the agent session. For writes, space_id is a debug/test override only and a mismatch is rejected (switch spaces first). For reads (including tier="catalog"), space_id is ignored — the space always resolves from the session. Actions and their key parameters: get key (tier="catalog" + catalog_entry_id reads a governed entry) set key, value, ttl, topic, content_type/render_as. The key's file extension drives artifact rendering (chart.svg -> SVG); inline HTML is inferred, and explicit content_type/render_as can make no-extension keys render as text/*, JSON, XML, or SVG artifacts when the value is inline content, a URL/data URL locator, or a dict with html/content/body/text/data. content_type takes precedence over render_as; artifact_type applies only to governed catalog writes. list prefix, topic, limit, offset (tier="catalog" lists governed entries) delete key approve key; re-saves the current entry without ttl so a pending document/entry is kept permanently. Backend GET errors are preserved instead of being reported as missing entries. decline key; removes a pending document/entry and refreshes the list terminate keys | key | prefix | topic promote key, to ("vault" default | "catalog"). Pass the source key as `key` (same as vault promote); to="catalog" also takes title/artifact_type. create title, artifact_type, artifact_value (or sha256+size_bytes). Catalog-only: unlike `set` it always requires title+artifact_type; `value` is accepted as an alias for artifact_value. act catalog_entry_id, action_id, base_artifact_version_id, base_state_version_id patch catalog_entry_id, patch, base_artifact_version_id, base_state_version_id Plain ephemeral usage needs only key/value/ttl/topic; the governed-catalog params apply only to create/act/patch, promote(to=catalog), tier=catalog reads.
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  • Create a serverless/standard/stateful workload — or a SCHEDULED JOB by setting `type: "cron"`. Define the container(s) in the typed `containers[]` array (the only way — there are no flat image/cpu/port fields) and scaling in the single `autoscaling` block. For a cron workload set `type: "cron"` and a required `schedule` (plus optional job policy); autoscaling/capacityAI/timeoutSeconds/debug do not apply to cron and are rejected. Decide reachability IN THIS CALL: a user-facing service needs `public: true` (or an explicit `firewallConfig`); omitted = deny-by-default, no internet access — do not create closed and patch the firewall afterward. Use the production-grade defaults from get_cpln_rules: explicit readiness + liveness probes, minScale ≥ 2 for user-facing services, CPU/memory sized to the runtime (NOT the platform defaults of 50m / 128Mi), autoscaling metric matched to traffic shape, never scale-to-zero unless the user asked for it by name. Type and name are immutable — changing either = delete + recreate. For databases / caches / queues / brokers / search / gateways / WAF / S3-compatible storage, propose the matching Template Catalog entry first (see get_cpln_rules). Recommended reading before first use: get_cpln_skill("workload") — the runbook for this tool family (read once per session).
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  • Update an existing workload (PATCH semantics — only specified fields change). Workload type and name are IMMUTABLE: trying to change either via update fails — those require delete + recreate. If the target is a CRON workload, patch its `schedule` / job policy / `suspend` / containers here (autoscaling/capacityAI/timeoutSeconds/debug do not apply to cron and are rejected); schedule/job fields are likewise rejected against a non-cron workload. Call get_resource (kind="workload") first to capture current state so a rollback exists. Avoid silent downgrades (probes, autoscaling) — see the production-grade defaults in get_cpln_rules. Advanced spec sections (loadBalancer, sidecar, extras, localOptions, rolloutOptions, securityOptions, requestRetryPolicy) are NOT here — use the matching configure_workload_* tool. Recommended reading before first use: get_cpln_skill("workload") — the runbook for this tool family (read once per session).
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  • Structure multi-step debugging and planning across tool calls — not a one-shot think. Tracks hypotheses, observations, plans; detects loops via lastActions; riskLevel high/critical blocks dangerous edits (drop table, prod deploy). Loads projectBrief (stack, key_paths, project_memory recall) on local project. On close, suggestedRemember → call project_memory remember. 4 credits hosted. Hard cap 10 thoughts/session. Call when: stuck after 2+ failed debug attempts, auth/billing/schema change spans 3+ files, flaky test you cannot explain, or you need a plan before editing. Pass lastActions (2–5 recent tool calls), goalAnchor after thought 2, sessionId to resume, area for subsystem. NOT when fix is known, single typo, repeating without new evidence, or session ended (nextThoughtNeeded:false). Read thoughtConfirmed and shouldContinue first. Legacy alias: thinking. Example: keep_thinking({ thought: 'Hypothesis: refresh token not rotated in middleware', thoughtType: 'hypothesis', thoughtNumber: 1, totalThoughts: 5, nextThoughtNeeded: true, confidence: 0.6, goalAnchor: 'Fix auth logout loop', lastActions: ['find_code(query=refreshToken)', 'read_code(target=authMiddleware)'], area: 'auth' }). Read-only.
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  • Elixir lint / debug kit: POST {code}, get the bugs back with line numbers. Deterministic static analysis — code is parsed, never executed, no AI. Catches unbalanced do/end and brackets, missing do, 'return', '+' string concat, trailing commas, field assignment, = vs == in conditions and guards, block-scoped rebinding (the classic), charlist vs String mixups, unused variables. Errors, warnings and hints with fixes. Max 128 KB. ($0.002 per call, paid via x402)
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  • Core dossier check: Trace the full HTTP redirect chain starting from https://<domain>/, recording each hop's status code and destination URL. Use to debug redirect loops, verify HTTP→HTTPS upgrades, or audit link shorteners; stops at 10 hops to prevent infinite loops. Follows Location headers with fetch (no auto-redirect), 5 s per hop. Returns a CheckResult: on success, {status:"ok", hops:[{url, statusCode, redirectsTo},...], final}; on failure, {status:"error", reason}.
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  • Validate a signed invoice against the ZATCA compliance/invoices endpoint WITHOUT fiscally reporting or clearing it — used during EGS onboarding to confirm your CSID + invoice structure pass ZATCA checks. Same envelope { invoiceHash, uuid, invoice(base64 signed UBL) }; no fiscal effect regardless of mode. Result carries validation_status plus any warnings/errors; reporting_status / clearance_status echo how ZATCA would treat the document. Use this to debug an invoice before calling report_invoice or clear_invoice. Required credential headers (set once in your MCP client, per-request, never stored): x-zatca-csid-token (your CSID binarySecurityToken) + x-zatca-csid-secret (its secret) — sent as HTTP Basic auth to ZATCA. Optional header x-zatca-mode: developer (default, sandbox, no fiscal effect) | simulation | core (production, real fiscal effect). Optional owner-policy headers x-agentpay-max-amount / x-agentpay-approval-above / x-agentpay-allowed-tools.
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  • Core dossier check: Trace the full HTTP redirect chain starting from https://<domain>/, recording each hop's status code and destination URL. Use to debug redirect loops, verify HTTP→HTTPS upgrades, or audit link shorteners; stops at 10 hops to prevent infinite loops. Follows Location headers with fetch (no auto-redirect), 5 s per hop. Returns a CheckResult: on success, {status:"ok", hops:[{url, statusCode, redirectsTo},...], final}; on failure, {status:"error", reason}.
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  • Core dossier check: Trace the full HTTP redirect chain starting from https://<domain>/, recording each hop's status code and destination URL. Use to debug redirect loops, verify HTTP→HTTPS upgrades, or audit link shorteners; stops at 10 hops to prevent infinite loops. Follows Location headers with fetch (no auto-redirect), 5 s per hop. Returns a CheckResult: on success, {status:"ok", hops:[{url, statusCode, redirectsTo},...], final}; on failure, {status:"error", reason}.
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  • List all skill bundles — named groups of tools the agent typically uses together for a single user intent (build-flow, debug-flow, monitor-flow, discover, governance). Returns each skill's description and member tool names. Call this first when you are unsure which tools apply to a request; then call tool_search with query: "skill:<name>" to load the full bundle. Non-billable.
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  • Test a message against an AI filter to check whether it would match. This tool embeds the provided message using Voyage AI and computes the cosine similarity between the message vector and the filter's stored reference vector. It returns the similarity score, whether the message would match (similarity >= threshold), and the filter's threshold value. Use this to: - Verify a filter works as intended before using it in a trigger - Tune the threshold by testing borderline messages - Debug why a message did or did not match a filter in production Returns: {similarity: float, matched: bool, threshold: float} Note: This tool calls the Voyage AI embedding API to embed the test message.
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  • Core dossier check: Retrieve and parse a domain's SPF record, decomposing it into mechanisms and qualifiers. Use to verify email sender policy, debug delivery failures, or check the 10-lookup limit; pair with dossier_dmarc for full email-auth coverage, or use dns_lookup with type=TXT for the raw record only. Fetches TXT records via Cloudflare DoH (1.1.1.1), 5 s timeout, locates the v=spf1 record and parses all mechanisms. Returns a CheckResult: on success, {status:"ok", raw, mechanisms:[{type, value, qualifier},...], lookupCount}; on failure, {status:"error", reason}.
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  • Check what primary ENS name is set for a wallet address (reverse resolution). Returns the ENS name that this address resolves to, or null if no primary name is set. This verifies both directions: - Reverse: address → name (the reverse record) - Forward: name → address (confirms the name actually points back to this wallet) If either direction is missing, the primary name won't resolve. Use this to: - Verify a primary name was set correctly after set_primary_name - Check if a wallet has any primary name configured - Debug why a primary name isn't showing up (missing ETH address record)
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  • Return console.log/warn/error events captured since the last drain. Filter by level ('log'|'info'|'warning'|'error'|'debug') and/or pattern (regex). Buffer caps at 500 entries; oldest are dropped first. Set clear=false to peek without draining.
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