"How to view console logs in a development environment" matching MCP tools:

• tflogs

  InsideOut (Riley)

  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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• dossier_ct_log

  drwho.me developer tools

  Core dossier check: Discover subdomains visible in Certificate Transparency logs. Use for attack-surface mapping; prefer dossier_full when running a complete audit. Queries crt.sh first, falls back to certspotter; capped at 100 unique subdomains; 10s timeout. Returns a CheckResult with { subdomains[], wildcards[], certCount, source }.

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• listMetricDefinitions

  Cortex

  List all available engineering metric definitions. USAGE - Call this endpoint BEFORE querying metrics (queryPointInTimeMetrics): 1. Once at start: Call with view='basic' to discover all available metrics - cache this response 2. Once per metric: Call with view='full' and key=METRIC_KEY to get detailed metadata - cache each response 3. Use cached metadata to construct valid point-in-time queries Cache responses in your context. Only refresh if no longer in your context window or explicitly requested (ex to check if metric readiness has changed). Query parameters: - view: 'basic' (default) returns minimal info, 'full' includes sources and query metadata - key: Filter metrics by key (supports multiple values and comma-separated lists) Full view provides query construction metadata: - supportedAggregations: Valid aggregation methods for the metric - orderByAttribute: Attribute path for sorting by metric values - groupByOptions[].key: Valid groupBy keys (use exact values, do NOT guess) - filterOptions[].key: Valid filter keys (use exact values, do NOT guess) Valid orderBy attributes for metric queries: - orderByAttribute: The metric value itself (returned in full view) - Source attributes: Any attribute from the metric's source (e.g., "source_name.attribute_name") - Dimension attributes: Any attribute from related dimensions (e.g., "source_name.dimension_name.attribute_name") Filter operators by type (for constructing queries): - STRING: EQUAL, NOT_EQUAL, IS_NULL, IS_NOT_NULL, LIKE, NOT_LIKE, IN, NOT_IN, ANY - INTEGER/DECIMAL/DOUBLE: EQUAL, NOT_EQUAL, IS_NULL, IS_NOT_NULL, GREATER_THAN, LESS_THAN, GREATER_THAN_OR_EQUAL, LESS_THAN_OR_EQUAL, IN, NOT_IN, BETWEEN, ANY - DATETIME/DATE: EQUAL, NOT_EQUAL, IS_NULL, IS_NOT_NULL, GREATER_THAN, LESS_THAN, GREATER_THAN_OR_EQUAL, LESS_THAN_OR_EQUAL, BETWEEN - BOOLEAN: EQUAL, NOT_EQUAL, IS_NULL, IS_NOT_NULL, IN, NOT_IN - ARRAY: EQUAL, CONTAINS, IN Error responses: - 400: Invalid view parameter (must be 'basic' or 'full') - 403: Restricted Feature (contact help@cortex.io)

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• switch_dannet_server

  dannet

  Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")

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• tfstatus

  InsideOut (Riley)

  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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• dossier_ct_log

  drwho.me

  Core dossier check: Discover subdomains visible in Certificate Transparency logs. Use for attack-surface mapping; prefer dossier_full when running a complete audit. Queries crt.sh first, falls back to certspotter; capped at 100 unique subdomains; 10s timeout. Returns a CheckResult with { subdomains[], wildcards[], certCount, source }.

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• save_note

  anamnese

  Save a new note with learned knowledge or procedures. Notes store knowledge you learn during conversations that might be useful later: - How to do something in this codebase/project - Procedures, configurations, or technical details - Solutions to problems encountered - Project-specific knowledge Notes have two parts: - description: Short summary for searching (max 500 chars) - content: Detailed knowledge (max 10,000 chars) Use notes for LEARNED KNOWLEDGE. Use facts for TRUTHS ABOUT THE USER. Examples: - description: "How to deploy this Next.js project to Vercel" content: "1. Run 'vercel' command... 2. Configure environment variables..." - description: "Database migration process for this project" content: "Migrations are in supabase/migrations/. To apply: npx supabase db push..." SELF-LEARNING (scope="ai_client"): Your persistent memory across conversations. Save a note whenever you learn something worth remembering — don't wait, save as you go. Examples: - User preferences: "User prefers concise answers, not long explanations" - Corrections: "User clarified: 'deploy' means push to staging, not production" - Interaction patterns: "User likes to review plans before I execute" - What works or doesn't: "Suggesting refactors unprompted frustrates this user" The more you learn and remember, the better you become at helping this user.

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• papers.list

  Urantia Papers

  List all 197 papers in the Urantia Book with their metadata (id, title, partId, labels). Use toc.get for a hierarchical view instead.

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• tflogs

  InsideOut (Riley)

  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_aggregation_view

  mcp-server

  Creates a materialized view or stored procedure in the project's BigQuery data warehouse for data pre-aggregation. **When to use this tool:** - When the user needs to pre-aggregate data from multiple connectors (e.g., cross-channel marketing report) - When a query is too slow to run on-demand and benefits from materialization - When the user asks to "create a view", "save this as a table", "materialize this query" **Naming rules (enforced):** - Target dataset MUST be 'quanti_agg' (created automatically if it doesn't exist) - Object name MUST start with 'llm_' prefix (e.g., llm_weekly_spend) - Format: CREATE MATERIALIZED VIEW quanti_agg.llm_name AS SELECT ... **SQL format:** - CREATE MATERIALIZED VIEW: for pre-computed aggregation tables - CREATE OR REPLACE MATERIALIZED VIEW: to update an existing view - CREATE PROCEDURE: for complex multi-step transformations **Example:** CREATE MATERIALIZED VIEW quanti_agg.llm_weekly_channel_spend AS SELECT DATE_TRUNC(date, WEEK) as week, channel, SUM(spend) as total_spend FROM prod_google_ads_v2.campaign_stats GROUP BY 1, 2 **Limits:** Maximum 20 active aggregation views per project.

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• tfstatus

  InsideOut (Riley)

  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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• agent_profile

  Swarm Tips — Aggregated AI Agent Activities

  [IN DEVELOPMENT] [READ] Trustless on-chain reputation lookup. Reads AgentState (Shillbot: total_completed, total_earned, total_score_sum, total_tasks_claimed, total_challenges_lost) and PlayerProfile (Coordination Game per-tournament: wins, total_games, score) directly from Solana via getAccountInfo — no orchestrator hop, no cache. Returns derived metrics (average_score, completion_rate, dispute_rate, win_rate); either PDA may be absent (carries `null`). Pass `wallet` to query an agent; omit for your registered wallet. `tournament_id` defaults to 1.

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• setup_account

  Hatchable

  Associate an email and handle with your account. Step 1: Call with just email — sends a 6-digit verification code. Step 2: Call with email + code + handle — verifies and completes setup. This lets you log in to the console and sets your permanent @handle.

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• bitrix-app-development-doc-details

  Bitrix MCP

  Fetch Bitrix24 app development documentation by exact title (use `bitrix-search` with doc_type app_development_docs). Returns plain text labeled fields (Title, URL, Module, Category, Description, Content) without Markdown.

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• search_data

  Opendata Ademe

  Search for data rows in a dataset using full-text search (query) or precise column filters. Returns matching rows and a filtered view URL. Use to retrieve individual rows. Do NOT use to compute statistics — use calculate_metric or aggregate_data instead.

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• search_data

  Opendata Koumoul

  Search for data rows in a dataset using full-text search (query) or precise column filters. Returns matching rows and a filtered view URL. Use to retrieve individual rows. Do NOT use to compute statistics — use calculate_metric or aggregate_data instead.

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• agent_trust_score

  Swarm Tips — Aggregated AI Agent Activities

  [IN DEVELOPMENT] [READ] Composite trust score (0..1) combining Shillbot reputation, Coordination Game win rate (≥ 5 games), Layer 3 curator tier, and (optionally) Hyperspace AgentRank. Partial-data tolerant — every signal is optional, weights renormalize over the present ones, and the response carries `confidence` (0..=4, how many signals contributed). Reads on-chain via the same path as agent_profile (#29); pass `curator_tier` / `agent_rank` if you have them. Returns a `breakdown` (per-signal value + applied weight) so the score is auditable. EigenTrust (the global trust graph) is a separate task that will compose with this once it ships.

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• development_appraisal

  property-finance-mcp

  Run a UK property development scheme viability appraisal. Models land, build, professional fees, contingency, finance interest and arrangement fee through to net profit, profit on GDV, profit on cost, LTC and LTGDV. Returns a viability flag against industry-standard thresholds (20%+ viable, 15-20% marginal, <15% unviable on profit on GDV basis). Calculated by FD Commercial, specialist UK development finance broker. Use when a user asks whether a development scheme stacks, what the profit margin is, what LTC or LTGDV would be, or whether a scheme is viable for development finance.

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• deploy

  Hatchable

  Deploy the project. Runs migrations/*.sql (tracked so each runs once), runs seed.sql on first deploy, copies public/ files to the CDN, and registers api/ files as live endpoints. Increments the project version. Always populate `intent` and `summary` so the user sees a readable changelog in the console: - `intent` is what the USER asked for, in their own words. Quote or lightly paraphrase their last instruction. e.g. "Add a split-the-bill section", "Make the buttons rounder". - `summary` is what YOU did, in plain language they can read. 1–3 sentences. e.g. "Added a SplitBill component with a member counter and per-person breakdown. Updated the main page nav to switch between solo and split modes." These become the commit message AND the History row title in the console. A user will likely scroll their History a week from now to remember what they built — write the summary so a future-you-with-no-context understands what shipped. If there is no clear user prompt (autonomous maintenance), leave `intent` blank but still pass a `summary` describing what changed and why. Call this after writing all your files. To verify your functions work after deploying, use `run_function` — it calls the function directly through your authenticated session and works for all project visibilities. The `url` field is the public URL for end users — personal projects require visitors to sign up before they can view the site.

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• donate

  Blueprint Agentic Staking (Solentic)

  Build an unsigned SOL transfer to support Blueprint development. Blueprint provides free staking infrastructure for AI agents — donations help sustain enterprise hardware and development. Same zero-custody pattern: unsigned transaction returned, you sign client-side. Suggested amounts: 0.01 SOL (thank you), 0.1 SOL (generous), 1 SOL (patron).

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