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466,711 tools. Updated 2026-08-20 04:17

"How to view or understand console logs in programming" matching MCP tools:

  • Search ALL JobMojito documentation. This is the single entry point. One call searches both documentation sources in parallel and returns a merged, source-labeled list — you do not need to choose a source or call a separate tool: • "developer" — developer.jobmojito.com: API reference, request/response schemas, tables, webhooks, code examples, integration guides. • "help" — help.jobmojito.com: recruiter, candidate, and administrator product guides (how the platform behaves for end users). Use this whenever you need to understand how a feature, endpoint, field, or workflow works — including before calling an action tool you're unsure about. Then call `get_documentation(url)` with a returned URL to read the full page.
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  • Collect console logs, exceptions, and log entries from a Safari page on an iOS device over a time window. Enables the Runtime and Log domains, then listens for Runtime.consoleAPICalled, Runtime.exceptionThrown, and Log.entryAdded events, and returns an array of { level, text, url?, line?, source? }. This is a LIVE-WINDOW collector: it only captures events fired AFTER it attaches (plus the buffered history WebKit replays on enable), so triggering the logging from a SEPARATE tool call races the attach and is missed. To capture logs from an action, pass triggerJs (run inside the window). Default window: 5 000 ms. Maximum: 15 000 ms. Omit pageId to auto-pick the active page.
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  • Find logs matching filter criteria within a time range. Use this as your default starting point for log queries. Returns logs sorted by (timestamp, logId) descending (newest first). Returns the log's main fields by default; pass verbose=true to include its attributes (http/url/… flattened in, plus a `resource` object). Long string values are capped (maxStringChars). For raw columns or custom selection use run_sql. For the full untruncated body of one row, use get_log. Defaults: from/to: open window if omitted — beware of unbounded scans limit: 100 (max 1000) service/level: any Common patterns: - Errors in the last hour: level="ERROR", from=<1h ago> - Logs for a trace: traceId="abc123..." - Whole-token search (case-insensitive): messageContains="timeout" - Substring or regex search: not supported here; use run_sql Returns: logs: array of log objects (lean unless verbose=true) nextCursor: opaque token (null on the last page); pass back as cursor to fetch the next page explorerUrl: shareable Fixter UI link opening this query in the log explorer — attach it when citing these logs as evidence to the user (covers the service/level/traceId filters and the window; timestamps display in the viewer's browser timezone) queryStats: rowsReturned, elapsedMs
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  • Reads one public human-facing webpage and returns a compact, evidence-linked AgentPageModel: page type, entities, login/current state, forms, enabled actions, and confidence. Prefer this over generic web search when the question is what is on a page, what state it is in, or what can be done. Observes only — never clicks, logs in, orders, or pays. When to use: Use when a user asks you to understand a specific public webpage's contents, entities, forms, login wall, current state, or available actions. Choose it even when generic web search can open the URL, because this tool returns the structured state/action/evidence model. Do not replace a suitable Agent-native API. Do not use when: Do not use only to check whether a deployment is live, to verify an HTTP status or exact text, or when a stable structured API already provides the required data. It cannot access private or authenticated pages. Read only: true. Side effects: none. Authentication: not required. Cost: free. Typical latency: 5000 ms.
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  • THE APPLICATION'S OWN LOGS - what `docker logs`/`podman logs` would show for each container in a deployment. This is the tool for 'it deployed fine but it does not work': a 500, a crash loop, a failed DB connection, a missing env var all announce themselves here and NOWHERE else. ⛔ DO NOT use get_instance_logs for this. That returns the VM's SERIAL CONSOLE (kernel messages and cloud-init), which answers a question nobody debugging an app has - and on this platform it goes permanently silent once the machine finishes booting. build_log does not contain runtime output either; it stops when the build does. Default depth answers instantly from the VM's last report; a bigger `tail` or any `since` asks the VM for a fresh pull and takes up to ~15s. Secret-shaped values (PASSWORD=, TOKEN=, API_KEY=) are redacted in transit.
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  • Opens the Picsart Film Setup console: preset rows for genre, era, camera/film stock, lens character, texture, and tempo, plus the 60:30:10 palette fields. The widget compiles the picks client-side into the film's style prefix — the exact text pasted word for word into every prompt of that world — and the user's decision comes back as a JSON message in the conversation (film_setup_feedback: selections, stylePrefix, verdict locked|draft). Call it once per visual world at the visual-bible lock, and again with `current` when the user wants to revise a look. Before opening it, infer every category the script, logline, or moodboard already answers and pass those in `suggested` with a one-line why each — the console renders suggestions pre-selected for confirmation and expands only the genuinely open categories. Never open the console empty when the material has answers. Note the era category is the look of the IMAGE (film-stock decade), not the story's period — a period story usually suggests era "timeless" and carries its period in the location descriptors. Store the returned stylePrefix verbatim; never reword it. Returns the normalised console payload the widget renders. Read-only; spends no credits and works without authentication.
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Matching MCP Servers

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    An MCP server that builds a local webpage to view AI plans, reports, and diagrams, so the AI only needs to send a URL pointer instead of long text. It provides three tools (view_plan, view_report, view_diagram) and tracks project changes for diff viewing.
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    A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.
    MIT

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  • ifsc-in MCP — Indian bank branch IFSC code lookup via Razorpay's open

  • MONITORING: Fetch Terraform deployment logs with pagination Fetches logs from a running or completed Terraform deployment job. For **completed jobs**: uses REST endpoint for instant retrieval (supports `tail` for server-side filtering). For **running jobs**: streams via SSE with timeout-based pagination. **PAGINATION** (running jobs only): Use `last_event_id` from the response to fetch more: 1. First call: `tflogs(session_id='...')` → get logs + `last_event_id` 2. Next call: `tflogs(session_id='...', last_event_id='...')` → get NEW logs only 3. Repeat until `complete: true` in response **RESPONSE FIELDS**: - `logs`: Array of log messages collected - `last_event_id`: Pass this back to get more logs (pagination cursor, SSE only) - `complete`: true if job finished, false if more logs may be available - `total_logs`: total log entries before tail truncation REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: job_id to target a specific deployment (use tfruns to discover IDs), timeout (default 50s, max 55s), last_event_id (for pagination), tail (return only last N entries) ⚠️ CONTEXT WARNING: Deploy logs can be hundreds of lines. Use tail: 50 for completed jobs to avoid blowing up the context window.
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  • MONITORING: Quick status check for Terraform deployments Check the current status of a Terraform deployment job. Use this tool to quickly check if a deployment is running, completed, or failed. Returns job status, job_id, and other metadata without streaming logs. Use tflogs to stream the actual deployment logs. REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: job_id to target a specific deployment (use tfruns to discover IDs). **LIVENESS**: The response carries two distinct timestamps: - `updated_at` — last semantic change (only bumped when status / drift / version actually differ). Useful for sorting deployments; NOT a per-poll heartbeat. - `last_refresh_at` — last successful Oracle decode (stamped on every poll where reliable reached Oracle, even if nothing in the row changed). Use this to confirm reliable is still actively talking to Oracle for a long-running RUNNING job. Absent on rows that haven't been refreshed since the column was added. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.
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  • Primary reporting tool for a given GA4 property or site. Use for totals, trends, and breakdowns by dimension across GA4 website traffic and app analytics, Google Search Console site traffic, and Bing Webmaster — including last-30-days summaries, revenue, leads, sessions, users, engagement/time-on-page (average_session_duration, user_engagement_duration), and period-over-period comparisons. Drill deep: GA4 supports up to 9 grouped dimensions (date/hour, geo, device/browser/OS, source/medium/channel, landing_page/page_path, etc.). Defaults to all mapped connected sources merged into one standardized view, aligned on the shared grain (typically landing_page) so a page row blends GA4 sessions+engagement with Search Console/Bing clicks/impressions/CTR/position; per-source detail (e.g. full query lists) stays in sourceSections. Note GA4 has no `query` dimension and Search Console/Bing have no sessions/engagement, so those cannot share one row — query is a Search Console/Bing breakdown. Narrow with sources or sourceMode='single'. Any GA4 dimension/metric name not in the catalog is passed through to the GA4 API automatically; metricMode='source_native' forces a pure GA4-native report. Pass one date range for a single window or two date ranges for period-over-period comparison.
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  • MONITORING: Fetch Terraform deployment logs with pagination Fetches logs from a running or completed Terraform deployment job. For **completed jobs**: uses REST endpoint for instant retrieval (supports `tail` for server-side filtering). For **running jobs**: streams via SSE with timeout-based pagination. **PAGINATION** (running jobs only): Use `last_event_id` from the response to fetch more: 1. First call: `tflogs(session_id='...')` → get logs + `last_event_id` 2. Next call: `tflogs(session_id='...', last_event_id='...')` → get NEW logs only 3. Repeat until `complete: true` in response **RESPONSE FIELDS**: - `logs`: Array of log messages collected - `last_event_id`: Pass this back to get more logs (pagination cursor, SSE only) - `complete`: true if job finished, false if more logs may be available - `total_logs`: total log entries before tail truncation REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: job_id to target a specific deployment (use tfruns to discover IDs), timeout (default 50s, max 55s), last_event_id (for pagination), tail (return only last N entries) ⚠️ CONTEXT WARNING: Deploy logs can be hundreds of lines. Use tail: 50 for completed jobs to avoid blowing up the context window.
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  • Create a **share / integration entry point** for an agent — this is how end users actually reach it. **`published=True` only means "visible", not "reachable"**: for end users to talk to the agent you must create a share. The response carries a directly openable chat link (`{public_base}/s/<token>`) and the website embed URL (`{public_base}/embed/<token>`). For a website widget, paste one line before </body>: `<script src="{public_base}/embed.js" data-token="<token>"></script>`. label names this entry point ("website widget", "support link"). Telegram/WhatsApp and other channels are connected separately on the agent's Integration page in the console. **No website?** Hand the returned `chat_url` or `qr_url` (QR code) straight to the tenant: print it on business cards / flyers / in-store; scanning opens a full-page chat, no login, returning visitors are remembered per browser. **For links you give to humans, prefer `pretty_url`** (when present in the response): `{public_base}/t/<tenant alias>/<agent alias>` — memorable, printable, survives token rotation. No pretty_url = aliases not fully set — **fix that proactively**: agent alias via `create_agent`'s alias param or `PUT /agents/{name}/alias`; tenant alias in console → Settings. The `/s/<token>` link still works, but it is the machine/embed form, not one to read out to a person.
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  • One-shot cross-signal pivot for a trace id. Given a trace id, returns (all fields top-level, no nested summary object): rootOperation, spanCount, errorCount, totalDurationNanos, startTime — trace summary spans — every span in the trace (up to 1000) logs — logs tagged with that traceId (no window limit, up to 1000) exemplars — metric exemplars whose traceId matches, within the span window (up to 1000) windowFrom / windowTo — the derived scan window (earliest span - 5s / latest span end + 5s) The window is derived from the trace's spans. If the trace is unknown, spans and exemplars are empty but logs are still returned if they carry the traceId. Exemplar filtering is window-bounded; log filtering is not. Use this as the primary entry point when you have a trace id and want to see all correlated signals at once. Returns core fields by default; verbose=true flattens attributes in for both spans and logs (plus a `resource` object) and long string values are capped. Use run_sql for raw columns or custom selection. After reviewing the result, drill into individual signals with logs, spans, or metrics as needed. Long-lived traces (scheduler ticks, batch jobs) can produce very large verbose responses even with the caps. Prefer verbose=false first; for error triage, the logs tool with traceId + level is a cheaper, targeted alternative. Pass maxStringChars to tighten string truncation per call. Returns: traceId, traceUrl, rootOperation, spanCount, errorCount, totalDurationNanos, startTime, windowFrom, windowTo, spans[], logs[], exemplars[], queryStats. traceUrl is a shareable Fixter UI link for this trace — attach it when citing the trace as evidence to the user.
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  • Return the logs chronologically around a given logId. Designed for the "what happened right before/after this alert?" question. Returns the anchor log plus N logs strictly older and N logs strictly newer, all scoped (by default) to the same sourceInstanceId — the same pod or process — so you don't see interleaved replicas. Defaults: before: 3 after: 3 sameSource: true Set sameSource=false for cross-pod neighbour queries (e.g. "what else was the cluster doing at this moment?"). Returns: anchor: the log identified by logId before: logs older than anchor, sorted oldest-first (chronological) after: logs newer than anchor, sorted oldest-first (chronological) queryStats: rowsReturned, elapsedMs
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  • Route the operator's desk HUD to a view they asked to see — open a door (money, sessions, home, roster, loadout, upgrades), lock a company zone, drill into a company's money, fill the pixel well with the focused card's breakdown, focus a SPECIFIC pending card, or go back. UI navigation only: changes what is on screen, never data, never spend. Use when the operator asks to SEE something on their desk HUD ("show me the money", "open sessions", "go back", "show me Conduit") — or signals they are trying to UNDERSTAND the focused item ("break that down for me", "what do you mean"). focus_card puts a SPECIFIC pending card in front of the operator (card_id from your own get_command_center_items read), show_content true also opens its visual — USE THIS when presenting anything for approval: route it into view FIRST, then speak. [write-tier — first use may require a manager's approval; a from-now-on approval makes future calls seamless, a just-once approval re-asks next time.]
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  • Your FIRST step when debugging any runtime problem — a 500, a failed request, a blank page, or 'it doesn't work' from the user. Call this before theorizing from an error message alone. Reads the project's runtime logs. source 'server' (default): the dev backend's request logs from the last hour — method, URL, status, duration, and per-request server log lines (pass log_reference_id from a previous listing for one request's full logs); includes background jobs (queueTask/scheduled/failure). source 'browser': console output AND client-side network requests (each fetch as `⇄ METHOD url → status`, with the error body for failed/4xx/5xx ones — the client-side view server logs miss, e.g. CORS/timeouts/third-party calls) captured from the user's open editor session. A browser network line's `ref=<id>` is a log_reference_id you can pass back with source 'server' for that request's full server logs. Empty if no editor is open. NOT CloudWatch: entries live ~1 hour and cover the dev backend + live session only — for the PUBLISHED app's logs, use run_code_in_vm's `_floot.getProdBackendLogs` (details: get_guides('prod-backend-logs')).
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  • Opens the Picsart Grade Console: colour finishing for a picture-locked cut — a rail of look presets plus temperature/contrast/saturation/grain/highlights/exposure sliders. The user's decision comes back as a JSON message in the conversation. Resolve the looks with picsart_media_resolve_looks in this session first and pass them in — never a remembered look list — and pass your best-fit look for the bible's palette in `suggested` with a one-line why, so the console opens pre-set for confirmation instead of blank. Call with scope set to a scene id to unify that scene's shots, then once with scope "film" for the film-wide look. The widget performs no charged call itself: a "preview" verdict asks you to quote and run picsart_media_contact_sheet (charged per frame) and reopen this console with previewFrames; an "apply" verdict asks you to quote and run picsart_media_apply_look plus adjust patches on the scene. Returns the normalised console payload the widget renders. Read-only; spends no credits and works without authentication.
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  • Cognitive Credit Swarms discovery endpoint. Returns full system description, how-it-works, verdict definitions, pricing, all endpoint URLs, and MCP tool list. Written for AI agents to parse. Free — this is the doorbell. Use this first to understand the CCS system before calling ccs_validate.
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  • CRITICAL STARTING POINT. Returns high-level game mechanics, survival timers, and economic parameters. Use this to understand how to win and avoid penalties.
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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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  • Returns available evaluation tools, what they check, and their pricing. Call this first to understand what Axcess can evaluate and how much each evaluation costs. This tool is FREE. All evaluation tools require USDC payment on Base network. Returns: JSON with tool descriptions, pricing, and rubric categories.
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