"Categorizing messages such as emails or system logs" matching MCP tools:

• ai_extract

  x402 Bazaar

  Unstructured text → structured JSON, one call — Turn ANY text into clean, schema-enforced JSON: pass text= plus the fields you want (fields=name,email,price,date — up to 10) and get exactly those keys back, guaranteed-valid JSON via Claude structured outputs. Add list=true to extract EVERY repeated record (invoice lines, listings, table rows) as an array. Up to 16K chars per call. Not crypto-specific — the universal parse step for agent pipelines: pages, emails, receipts, logs. Many documents? ai-extract-batch: 10 in one call for $0.10. Required input: text. Priced $0.05 per call over x402 on Base; send a prepaid x-credit-token header for unlimited calls, or get 1 free call/day per tool. No wallet or API key required.

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• read_messages

  Roomcomm

  Read messages from a Roomcomm room. Core read operation for every tick of your polling loop. Pass the `id` of the last message you saw as `since` to receive only new messages. Omit `since` on the very first tick to get the full (or most recent) history. Returns {messages: [{id, agent_id, text, timestamp}], has_more}. Track the largest `id` as your new `last_id`. Args: uuid: Room UUID or full room URL. since: Return only messages with id > since. limit: Maximum messages to return (default 100, max 500). Example: read_messages("a1b2…", since=42) on each tick.

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• extract_ibans_from_text

  ibanchecker-mcp

  Scan a free-form block of text and pull out every candidate IBAN, then validate each one. Useful for unstructured sources such as emails, invoices, PDFs pasted as text, or chat messages where IBANs appear inline and may be split by spaces or surrounded by other words. Returns a JSON array of the IBANs found, each with its validation result (`valid`, `countryCode`, bank details when known); text containing no IBAN returns an empty list rather than an error. Use this as the first step when the account number is buried in prose; pass the extracted IBANs to `validate_bulk_ibans` only if you need to re-check them separately. Input text is processed in memory and not stored.

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• submit_response

  Ansvar: EU Compliance & Legal Intelligence

  Provide an answer to the current step in a compliance workflow. Use this when someone provides information requested by the workflow, such as 'our system processes health data' or 'we use AES-256 encryption'. The workflow engine validates the response and advances to the next step. Pass user_acknowledged=true only after the user has supplied the fields listed in user_provided_fields. evidence_references accepts document UUIDs, doc:// segment URIs, or regulatory URLs. For an unattended gate, pass approved_by='auto' and leave user_acknowledged=false so the report does not misrepresent automation as human review. approved_by accepts only 'auto'; human review is asserted via user_acknowledged, never by naming an approver.

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• logs

  Fixter

  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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• get_container_logs

  mcp

  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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• 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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• 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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• correlate

  Fixter

  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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• identify_reference_system

  DaedalMap Disaster and Geospatial Data

  Free geography utility. Checks a bounded sample of identifiers against maintained reference indexes and geometry banks. LLM clients must extract identifier values from the user's natural-language request and pass them as strings; do not put the prose question in the arguments, and preserve leading zeros. Use it when a caller has geography keys but is unsure which system, level, or bank they belong to, or wants to verify a declaration such as 2020 US Census tract GEOIDs. Returns ranked candidates, deterministic warnings, machine-readable clarification questions when evidence is incomplete or ambiguous, exact match and shape-availability counts, and a recommended geography_binding for estimate_conversion_job. It does not convert the full dataset or return polygons. No payment required.

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• portal_evm_query_logs

  SQD

  Query raw EVM logs with address/topic filters, common event aliases, earliest/latest scanning, and optional inline decoding. COMMON USER ASKS: - Recent USDC Transfer logs - First recent USDC Transfer log - Latest ERC721/pass mint ID and tx hash FIRST CHOICE FOR: - NFT or ERC721 mint lookups such as latest pass minted, token ID, and mint transaction hash - contract event questions where the user needs exact event evidence rather than wallet or transaction summaries WHEN TO USE: - You need event logs filtered by contract or topic signature. - You want decoded log hints while still keeping the raw log shape available. - You want the first or last matching event in a bounded block/time window. - You want common event names such as transfer, approval, swap, mint, or burn instead of remembering topic0 hashes. - You need the latest ERC721/pass mint in a bounded deployment/recent window: filter Transfer events with topic1 as the zero address, use scan_order=latest, limit=1, and decode=true to expose decoded_log.decoded.token_id plus transaction_hash. DON'T USE: - You only want token transfers, which are easier with the token-transfer tool. EXAMPLES: - Recent USDC Transfer logs: {"network":"base-mainnet","timeframe":"1h","token_symbols":["USDC"],"event":"transfer","limit":20} - First recent USDC Transfer log: {"network":"base-mainnet","timeframe":"1h","token_symbols":["USDC"],"event":"transfer","scan_order":"earliest","limit":1} - Latest ERC721/pass mint ID and tx hash: {"network":"base-mainnet","from_block":46020000,"to_block":46100000,"addresses":["0xE4E70FdF2Fc1147a7f35c4c5de88E6BeA63eeAfA"],"event":"transfer","topic1":["0x0000000000000000000000000000000000000000000000000000000000000000"],"scan_order":"latest","decode":true,"include_transaction":true,"limit":1} - Decode logs inline: {"network":"ethereum-mainnet","timeframe":"1h","topic0":["0xddf252ad1be2c89b69c2b068fc378daa952ba7f163c4a11628f55a4df523b3ef"],"decode":true,"limit":10}

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• get_doc

  SukukFi

  Return a full SukukFi documentation page as markdown. Call search_docs first to find a slug, or pass a known slug such as "for-capital-providers/risk-considerations".

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• get_store_template_details

  agentView

  Returns full details of one store template: localized title and description, long-form markdown, category, suite, tags, features, preview image and agentArtifacts (bot-onboarding files such as system prompts, Agent Skills SKILL.md, MCP config). Use after search_store_templates before recommending or installing; when agentArtifacts is non-empty, fetch bodies via get_agent_artifact. No authentication required.

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• gribstream_resolve_shared_parameter

  GribStream Weather MCP

  NO AUTH / PUBLIC / READ-ONLY. Resolves one shared parameter preset for a dataset, returning native variables and expressions to use in /timeseries or /runs request bodies. Use this first for common natural-language concepts such as 2 metre temperature or 10 metre wind instead of guessing dataset-native codes such as TMP. This tool does not execute the request, query weather values, or return forecast data.

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• read_messages

  roomcomm

  Read messages from a Roomcomm room. Core read operation for every tick of your polling loop. Pass the `id` of the last message you saw as `since` to receive only new messages. Omit `since` on the very first tick to get the full (or most recent) history. Returns {messages: [{id, agent_id, text, timestamp}], has_more}. Track the largest `id` as your new `last_id`. Args: uuid: Room UUID or full room URL. since: Return only messages with id > since. limit: Maximum messages to return (default 100, max 500). Example: read_messages("a1b2…", since=42) on each tick.

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• prepare_local_garment_upload

  Uwear

  First step for garment images on the host's local filesystem, such as files in ~/Downloads. Use only when the host can read those local files and perform the returned direct multipart HTTP uploads, such as Codex. Include every returned form field and send the file bytes under the returned file_field. Never send a local path to Uwear. Do not use this for ChatGPT attachments or existing public URLs. After every upload succeeds, call finish_local_garment_upload with the returned upload handles.

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• search_cves

  cve-intelligence

  Search the catalog. Free text (q) and/or structured filters: vendor (slug), cwe (CWE-nnn), technique (ATT&CK id, such as T1190), year ("2024,2025"), sev ("critical,high"), kev (0|1), kev_from / kev_to (ISO days, half-open CISA listing window; imply kev=1), kev_vendor (the CISA vendorProject string verbatim, such as "Microsoft"), ransomware (0|1), detect (0|1, a detection signal we track), fix (0|1; fix=0 means the fix status was computed and this dataset holds no actionable vendor fix), automatable (0|1, CISA SSVC Automatable; 1=yes, 0=CISA assessed no, unassessed CVEs match neither), epss_gte (0..1), eco (OSS ecosystem, such as npm or PyPI), pkg (pkg_key, such as npm/lodash; for ranges use query_package), page, limit (1..50). Filter-only queries return the /browse slice ordered KEV-first then EPSS.

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• check_compliance

  ExpenseBot

  Use only when the user explicitly asks to check an existing report for compliance issues such as missing business purpose or policy violations. Creating a report, excluding Personal expenses, sharing a report, or billing a client is not a compliance request; never call this tool automatically as a preflight or follow-up for those workflows.

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• get_app_status

  AppDeploy

  Use this when deploy_app returns, when checking deployment status, or when the app has errors or is not working as expected. Returns deployment status, e2e test status, QA snapshot, and frontend/backend error logs; treat deployed_and_testing status as non-final, always inspect QA/errors, and call get_e2e_qa_run_details if e2e tests fail.

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• identify_reference_system

  DaedalMap Geography Tools (loc_id)

  Free geography utility. Checks a bounded sample of identifiers against maintained reference indexes and geometry banks. LLM clients must extract identifier values from the user's natural-language request and pass them as strings; do not put the prose question in the arguments, and preserve leading zeros. Use it when a caller has geography keys but is unsure which system, level, or bank they belong to, or wants to verify a declaration such as 2020 US Census tract GEOIDs. Returns ranked candidates, deterministic warnings, machine-readable clarification questions when evidence is incomplete or ambiguous, exact match and shape-availability counts, and a recommended geography_binding for estimate_conversion_job. It does not convert the full dataset or return polygons. No payment required.

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