"Assistance with Debugging Frontend Issues Using JavaScript Code" matching MCP tools:

• verify

  verify

  An outside check on code, executed in a sealed sandbox. Call it before code crosses a consequence boundary: before you merge it, deploy it, publish it, settle a payout on it, or report it done. A self-audit verifies consistency, never completeness: a check written inside the frame that produced the code passes on the code's own assumptions. This is the check that is not you. Also call it when a fix passes your own check but the target still fails; that means your check shares the code's assumption and cannot see the error. INPUT: code (JavaScript/Node or Python 3 source, deterministic only) plus ONE of: contract {fn, examples:[{call,expected}]} (copy call and expected from the test or spec the consequence depends on), or assumption (plain-language claim, weaker read). It checks the code against the contract exactly as given. VERDICTS (synchronous): BROKE: the code violates your contract, with the exact input and a rerunnable proof; do not proceed. HELD: the code meets the contract you gave; proceed on that contract, and nothing more. FINDINGS: a stated property strains under a generated input; check it before proceeding. DROP: not deterministically checkable. PAYMENT: 0.10 USDC per call, x402 v2 on Base, no account. Every delivered verdict is charged, HELD and DROP included. If no verdict is produced, the payment authorization is cancelled and you are not charged.

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• canary_scan

  canaryusers

  Run a CanaryUsers UX scan on a DEPLOYED URL (your live or preview app — not source code). A flock of AI personas evaluates the page and reports where real users would get stuck, with concrete fixes. Returns AI-ready findings you can act on immediately. Use depth='deep' for the thorough scan that renders the page, checks it VISUALLY on desktop + mobile (catches mobile breakage and layout issues), and clicks through key flows like signup/checkout (slower, ~60-90s, uses one credit); depth='quick' (default) is a fast static check that does NOT see mobile or visual issues — use 'deep' when the user mentions mobile, layout, or visual problems. IMPORTANT: if this returns status 'running' with a scanId, the findings are not ready yet — wait ~30s, then call get_report_markdown(scanId), repeating until it returns the report. Always fetch and present the findings before stopping, then offer to fix the top issues.

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• migrate_to_propelauth_frontend

  PropelAuth Integration MCP Server

  Returns instructions for migrating to PropelAuth in a frontend framework such as React, JavaScript, TypeScript, or when using Next.js for just the frontend (e.g. client-side rendered). Guidance includes migrating from several auth providers, such as Clerk or Auth0. Each guidance will include documentation from the auth provider and PropelAuth. It is important to follow the instructions carefully to ensure a successful integration. Make sure to use the 'Installation' guidance first. It is important to call every guidance to ensure a successful integration. Do not update a component/hook/etc from the auth provider until you receive guidance about that component/hook/etc. CRITICAL: If the current implementation uses a traditional OAuth/OIDC flow (e.g., via express-openid-connect, passport-auth0, or similar backend-managed session libraries), you MUST select 'OAuth' as the framework, regardless of the frontend library (React/Vue/etc.). Only select 'React' or 'Javascript' if the current implementation uses a frontend-only SDK (like @auth0/auth0-react) or if using fullstack Next.js.

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• migrate_to_propelauth_fullstack

  PropelAuth Integration MCP Server

  Returns instructions for migrating from an existing auth provider to PropelAuth in a fullstack Nextjs App Router or Nextjs Pages Router application. If the user is using Next.js as just a frontend (e.g. client-side rendered with or without server routes), use the migrate_to_propelauth_frontend tool. Guidance includes installation and configuration, retrieving user or org information, logging users out, redirecting users to login, and more. Make sure to use the 'Installation' guidance first. It is important to call every guidance to ensure a successful integration. Do not update a component/hook/etc from the auth provider until you receive guidance about that component/hook/etc

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• glim_github_search

  glim.sh

  Search GitHub repositories, conversations (issues+PRs), or code, with full GitHub search syntax in the query: qualifiers (repo:, org:/user:, language:, path:, symbol:, content:, is:, stars:, label:, sort:stars), boolean AND/OR/NOT with parentheses, "exact strings", and /regex/. kind='repos': MINIMAL distinctive keywords - the project/library name only ('rtk', 'react query'); every extra word must ALL match and buries the canonical repo - filter with qualifiers, not prose. kind='code': ONE literal code pattern as it appears in files ('useState('), an "exact string", a /regex/, or symbol:name to find definitions, across 2.8M+ public repos; narrow with repo:/language:/path:. Not supported in code search: license:, enterprise:, is:vendored, is:generated. kind='conversations': returns compact previews - use glim_github_get for full content; sort: REPLACES relevance ranking (words match anywhere incl. comments), omit it for best matches. Set repo='owner/name' to scope to one repository (works with any kind; with repos it routes to conversations). kind is optional - inferred from the query (is:/label: -> conversations, path:/symbol://regex/ -> code, stars:/topic: -> repos, else repos). Returns compact text by default; pass format='json' for full structured data.

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• run_code

  CoreModels

  Execute a JavaScript program that orchestrates this server's tools, and return only its result. Prefer this over many individual tool calls when a task needs several steps, looping, filtering, or combining data: intermediate results stay in the sandbox, so only what you return reaches the model. Inside the script: - listTools() -> [{name, summary}] discover available tools - getToolDoc(name) -> {name, description, parameters, required} inspect one tool's inputs - tools.<name>(args) -> parsed result call a tool (graphProjectId is injected automatically; do NOT pass it) - console.log(...) captured and returned alongside the result - return <value> JSON-serialized and returned Environment: sandboxed JavaScript, no network or filesystem, with limits on time, memory, statements and number of tool calls. Currently only read-only tools are callable from code.

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• discovery_signup_verify

  Disco

  Complete Disco signup using an email verification code. Call this after discovery_signup returns {"status": "verification_required"}. The user receives a 6-digit code by email — pass it here along with the same email address used in discovery_signup. Returns an API key on success. Args: email: Email address used in the discovery_signup call. code: 6-digit verification code from the email.

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• render_diagram

  Diagrams MCP

  Render a mingrammer/diagrams Python snippet to PNG and return the image. The code must be a complete Python script using `from diagrams import ...` imports and a `with Diagram(...)` context manager block. Use search_nodes to verify node names and get correct import paths before writing code. Read the diagrams://reference/diagram, diagrams://reference/edge, and diagrams://reference/cluster resources for constructor options and usage examples. Args: code: Full Python code using the diagrams library. filename: Output filename without extension. format: Output format — ``"png"`` (default), ``"svg"``, or ``"pdf"``. download_link: If True, return a temporary download URL path (/images/{token}) that expires after 15 minutes; if False, return inline image bytes. Defaults to True (URL) — set ``DIAGRAMS_INLINE_DEFAULT=true`` on the server to flip the default. SVG/PDF and PNGs larger than the inline limit always use a download link.

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• analyze_xero_journal_cleanup

  HelloBooks AI Agents

  Scan a Xero "Manual Journals" CSV export for cleanup issues — unbalanced journals, duplicate journals (same date + same totals), and schema problems (invalid dates, malformed amounts, missing account code/name, missing group key). Input is the raw CSV content the user pastes after exporting from Xero via Accounting → Advanced → Manual Journals → Export. Xero-specific idioms handled: signed Amount column (positive = credit, negative = debit), explicit Debit/Credit fallback shape, Reference-or-Narration+Date grouping, account code preferred over name. Max 5,000 rows; max 5 MB. Returns structured flags with severity, a roll-up summary, parse diagnostics, and a shareable URL at agents.hellobooks.ai/r/{slug}. Use this when a user pastes Xero manual-journal data, asks "check my Xero books", or "find issues in my Xero journal". The funnel CTA routes to /migrate/from-xero for users who want to fix at scale.

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• post_debug_code

  webbersites-x402-data-api

  LLM CODE DEBUGGING — POST {code, error} and get a diagnosis: what is wrong, the root cause, and a concrete fix with corrected code. Paste the failing snippet plus the error message or stack trace; any language, up to 20,000 chars combined. Optional {language} and {context} ('happens only on the second call'). Fast cheap LLM under the hood. Want deterministic no-AI lint instead? POST /api/lint/:language ($0.002). ($0.01 per call, paid via x402)

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• diagnose_error

  canton-ccpedia

  Paste a Canton/Daml/Splice ERROR MESSAGE, stack trace, or error code and get the most likely resolved fixes from CCPEDIA history: forum threads where the same error was discussed, related GitHub issues, and the SDK version range it appeared in. Needs a literal error string or code (e.g. TOPOLOGY_TOO_MANY_PENDING_TOPOLOGY_TRANSACTIONS, ValidatorLicense); do NOT use it for symptom descriptions with no error text (e.g. "my balance is zero"), use semantic_search for those. Canton-specific. Returns top 3 matches each from forum and github.

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• check_injection

  ContrastAPI

  Scan source code for injection vulnerabilities: SQL injection, command injection, path traversal via unsafe string concatenation/unsanitized input. Supports Python, JavaScript, TypeScript, Java, Go, Ruby, Shell, Bash. Use to detect input-handling bugs; for secrets use check_secrets. Companion code-security tools: check_secrets (hard-coded credential detection), check_dependencies (known-CVE vulnerability audit), check_headers (live HTTP security-header validation), scan_headers (live HTTP scan via domain). Free: 30/hr, Pro: 500/hr. Returns {total, by_severity, findings}. No data stored.

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• deploy_group

  Dockhold

  Deploy several connected services in one go (e.g. a frontend + an API). Call this when the user's project is split across multiple repos that must talk to each other; for a single repo use deploy_app. Each service is a public GitHub repo that gets its own URL. Wire them by setting an env var to the exact token ${services.<otherServiceName>.url} — Dockhold injects that service's live URL once it deploys. Give the backend its own database with "db":"enable" (DATABASE_URL is injected; a pure frontend doesn't need one). Builds run in parallel; poll get_app_status with each returned app_id.

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• execute

  mcp

  Runs JavaScript code to interact with the Mux API. You are a skilled TypeScript programmer writing code to interface with the service. Define an async function named "run" that takes a single parameter of an initialized SDK client and it will be run. For example: ``` async function run(client) { const asset = await client.video.assets.create({ inputs: [{ url: 'https://storage.googleapis.com/muxdemofiles/mux-video-intro.mp4' }], playback_policies: ['public'] }); console.log(asset.id); } ``` You will be returned anything that your function returns, plus the results of any console.log statements. Do not add try-catch blocks for single API calls. The tool will handle errors for you. Do not add comments unless necessary for generating better code. Code will run in a container, and cannot interact with the network outside of the given SDK client. Variables will not persist between calls, so make sure to return or log any data you might need later. Remember that you are writing TypeScript code, so you need to be careful with your types. Always type dynamic key-value stores explicitly as Record<string, YourValueType> instead of {}.

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• audit

  mcp

  Perform comprehensive audit of a website URL. Fetches the URL content ONCE and provides a combined report with: - Classification: category, subcategory, language, sentiment, demographics - SEO Analysis: score, grade, issues, recommendations - EEAT Analysis: experience, expertise, authoritativeness, trustworthiness scores - AEO Analysis: AI answer engine optimization score, metrics, issues, signals (includes full Citation Readiness analysis in the nested 'citation' key) - Advertiser Matching: best-fit advertising networks with scores - Similar Sites: competitor/related sites from the same category This is more efficient than calling classify_url, analyze_seo, analyze_eeat, analyze_aeo, select_advertiser, and find_similar_sites separately as it only fetches the page once. Args: url: The website URL to audit (e.g., "https://example.com"). Returns: Comprehensive audit report with: - url: The analyzed URL - classification: Category, subcategory, language, sentiment, demographics - seo: Score, grade, issues, recommendations - eeat: EEAT score, grade, category scores, issues, signals - aeo: AEO score, grade, metrics, issues, signals (includes citation results) - advertisers: Matched advertising networks with scores - similar_sites: Related sites from the same category (up to 10) - cached: Whether result was from cache

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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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• run_code

  coremodels

  Execute a JavaScript program that orchestrates this server's tools, and return only its result. Prefer this over many individual tool calls when a task needs several steps, looping, filtering, or combining data: intermediate results stay in the sandbox, so only what you return reaches the model. Inside the script: - listTools() -> [{name, summary}] discover available tools - getToolDoc(name) -> {name, description, parameters, required} inspect one tool's inputs - tools.<name>(args) -> parsed result call a tool (graphProjectId is injected automatically; do NOT pass it) - console.log(...) captured and returned alongside the result - return <value> JSON-serialized and returned Environment: sandboxed JavaScript, no network or filesystem, with limits on time, memory, statements and number of tool calls. Currently only read-only tools are callable from code.

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• submit_support_request

  Skala — Legal Platform for Startups

  Submit a support request to the Skala team on behalf of the user. Call this when the user needs human assistance that AI cannot provide, the question is too complex or high-risk, or the user explicitly asks for human support. IMPORTANT: Always confirm with the user before calling — describe what you will submit and ask for their approval. Before calling, compile the issue from conversation context into the description.

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• acc_list_issues

  ACC MCP

  List and filter issues from a single ACC project (limit 50 per call) via the APS Construction Issues API. When to use: The user or upstream agent needs to review open issues, count issues by status/priority, or look up an issue_id before calling acc_update_issue. E.g. 'show me all critical open issues on the Tower project'. When NOT to use: Do not use to fetch RFIs (use acc_list_rfis) or to search documents. APS scopes: data:read account:read. No write scope required. Rate limits: ACC Issues API ~100 req/min per app; results pageable (limit 50 here, max 200 upstream). For large projects, call once and filter client-side instead of looping. Errors: 401 (APS token expired — refresh); 403 (user lacks 'View Issues' permission on project or scope insufficient); 404 (project_id not found — verify 'b.' prefix and hub membership via acc_list_projects); 422 (invalid filter value — check status/priority spelling); 429 (rate limit — back off 60s); 5xx (ACC upstream — retry with jitter). Side effects: None. Read-only and idempotent.

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• post_lint_javascript

  webbersites-x402-data-api

  JavaScript / Node lint: POST {code}, get the bugs back with line numbers. Syntax errors come from the real V8 parser (compile-only — code is never executed), plus deterministic checks: loose == coercion, assignment in conditions, comparisons with NaN, const reassignment (runtime TypeError), var pitfalls, unused variables, leftover console.log. Handles ESM imports, template literals, regex. No AI. Max 128 KB. ($0.002 per call, paid via x402)

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