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MCP — Monitoring automations & extraction recipes

MCP namespace

Monitoring automations & extraction recipes

Configure end-to-end web and document monitoring jobs with MCP commands.

Monitoring tools let your AI configure structured scrapers, forward-download pipelines, and quality assurance steps without touching the UI. The same definitions used by the Midesk platform can now be orchestrated through MCP.

Teach your AI to set up and validate extraction jobs before data hits the repository.

  • Author extraction recipes for complex HTML and document layouts.
  • Validate selectors and clean transforms with preview/test commands.
  • Manage job lifecycle from creation to deployment entirely via MCP.

Available MCP tools

Ask your assistant to call these functions by name. Each tool mirrors the behaviour available in the Midesk interface so your automation stays compliant and auditable.

Configure Extraction

monitoring__configure_extractionMonitoring Automations

[STAGE 5: Configuration] Persist a tested extraction pipeline on a task (new or existing). Accepts normalized steps (jsonConditions supported). Returns examples, textual next_steps, and typed next_tools suggestions to continue testing and validation.

Parameters

  • job_id

    string

    Required

    Monitoring job ID

  • task_id

    string

    Task ID to update (leave empty to create new task)

  • task_name

    string

    Name for the task (required for new tasks)

  • data_type

    string

    Optional semantic label for the data (e.g., 'News article', 'Job posting', 'Price'). Used to derive a Data Type when none provided.

  • data_type_id

    string

    Optional: Explicit Data Type ID to use. When omitted, the tool infers a default type from steps/value type.

  • steps

    array

    Required

    Extraction steps. Examples: - Single value: [{"method":"xPath","pattern":"//title"}] - Multiple items + transform: [{"method":"xPath_extract","pattern":"//div[@class=\"item\"]"},{"method":"json","pattern":null,"jsonConditions":[{"function":"transform","key":"{\"title\":\"${ @step | xPath : \'//h2\' }\"}"}]}]

    Array items

    • [item]

      object

      Nested fields

      • method

        string (xPath, xPath_extract, json, regex, gpt)

        xPath, xPath_extract, json, regex, or gpt

        Allowed values: xPath, xPath_extract, json, regex, gpt

      • pattern

        string

        Extraction pattern. For json, set to null when providing jsonConditions.

      • jsonConditions

        string

        Optional stringified conditions for json step (filters, transforms). Will be decoded/normalized.

  • test_first

    boolean

    Test extraction before saving (recommended)

Configure Forward Download

monitoring__configure_forward_downloadMonitoring Automations

Enable or disable forward-download of articles for a task. When enabled, set the Story Channel to save downloaded articles into.

Parameters

  • job_id

    string

    Required

    Monitoring job ID

  • task_id

    string

    Required

    Task ID that will forward-download articles

  • download_articles

    boolean

    Required

    Enable forward-download of links into articles

  • story_channel_id

    string

    Story Channel ID (required when download_articles=true)

Create Monitoring Job

monitoring__create_monitoring_jobMonitoring Automations

[STAGE 2: Structure setup] Create a monitoring job (URL) once we previewed that URL and know we can extract data from it. Optional step - can test extraction first. Next: Use `monitoring__test_step` to develop extraction or `monitoring__configure_extraction` to add tasks.

Parameters

  • name

    string

    Required

    Name for the monitoring job

  • url

    string

    Required

    URL to monitor

  • data_model_name_or_id

    string

    Required

    Database name for storing raw results; typically an Entity name, such as Apple (creates if not exists)

  • data_type_name_or_id

    string

    Optional: Name or ID of Data Type (e.g., "Blog article"). If name does not exist, it will be created.

  • data_type_value_type

    string (Text, Json, Number, Date, Money, Boolean)

    Optional: Value type for new Data Type (defaults to Json).

    Allowed values: Text, Json, Number, Date, Money, Boolean

  • download_articles

    boolean

    Optional: Enable forward download of extracted links into Stories (articles).

  • story_channel_id

    string

    Optional: Story Channel ID to store downloaded articles in (required if download_articles=true).

  • initial_task_name

    string

    Optional: Name of the initial task to create when download_articles is enabled.

  • comment

    string

    Comment or description (optional)

Explore

monitoring__exploreMonitoring Automations

[EXPERIMENTAL] Unified tool for monitoring exploration. Preview data, test patterns, develop extraction pipelines - all in one place. Smart mode detection based on inputs.

Parameters

  • source

    string

    Required

    URL (https://...), job_id (numeric), or "cached"/"same" to reuse last data

  • pattern

    string

    Extraction pattern to test (optional). If not provided, shows data preview

  • method

    string (xPath, xPath_extract, json, regex, gpt)

    Extraction method (auto-detected if not provided)

    Allowed values: xPath, xPath_extract, json, regex, gpt

  • transform

    array

    Transformation mapping to apply after extraction (e.g., {"title": "@name", "price": "@cost"})

    Array items

    • [item]

      string

  • previous_results

    array

    Previous extraction results for chaining (internal use)

    Array items

    • [item]

      string

  • limit

    number

    Maximum results to show (default: 10)

Get Job Details

monitoring__get_job_detailsMonitoring Automations

Get complete configuration of a monitoring job

Parameters

  • job_id

    string

    Required

    Monitoring job ID

Get Transform Examples

monitoring__get_transform_examplesMonitoring Automations

Show transform pattern examples for common extraction scenarios (prices, dates, lists, nested data). Returns: Code examples with explanations.

This tool does not require any input parameters.

List Jobs

monitoring__list_jobsMonitoring Automations

List monitoring jobs.

Parameters

  • enabled_only

    boolean

Preview Data

monitoring__preview_dataMonitoring Automations

[STAGE 1: Discovery] Preview raw HTML/JSON from any URL to understand data structure. Shows content, patterns, and extraction suggestions. START HERE when building new monitoring. Next: Use `monitoring__test_step` to develop extraction.

Parameters

  • job_id

    string

    Monitoring job ID (optional - provide URL if no job exists)

  • url

    string

    URL to preview (required if job_id not provided)

  • disable_js

    boolean

    Disable JavaScript execution (faster but may miss dynamic content)

  • preview_size

    string (snippet, partial, full)

    How much data to return: snippet (first 5000 chars), partial (35000 chars), full

    Allowed values: snippet, partial, full

  • use_cache

    boolean

    Use cached data if available (faster, default: true). Set to false to force fresh crawl.

Test Extraction

monitoring__test_extractionMonitoring Automations

[STAGE 4: Testing] Verify saved extraction configuration works correctly. Use after `monitoring__configure_extraction`. Next: Use `monitoring__validate_monitoring_job` for production readiness and activation (automatically if all is validated).

Parameters

  • job_id

    string

    Required

    Monitoring job ID

  • task_id

    string

    Required

    Task ID to test

  • limit

    number

    Maximum results to show (default: 5)

  • show_steps

    boolean

    Show intermediate results for each step

Test Step

monitoring__test_stepMonitoring Automations

[STAGE 3: Development] Develop extraction pipelines iteratively. Test one step at a time (xPath, xPath_extract, regex, json, gpt), optionally chaining with previous_steps. Get immediate feedback, quality hints, and typed next_tools suggestions. When stable, save via `monitoring__configure_extraction`.

Parameters

  • job_id

    string

    Job ID to test against. Optional when url is provided. Use job to inherit recipe settings (JS, pagination).

  • url

    string

    URL to test. Required when job_id is not provided. When both supplied, URL overrides job URL for ad-hoc testing.

  • method

    string (xPath, xPath_extract, json, regex, gpt)

    Required

    Extraction method. Use xPath for single nodes, xPath_extract for lists, regex for cleanup, json for transforms/filters, gpt for semantic post-processing.

    Allowed values: xPath, xPath_extract, json, regex, gpt

  • pattern

    string

    Required

    Pattern to test. xPath: //div[@class="price"], regex: /\d+/, json: a transform template like ${ title } or full JSON object template, gpt: a clear instruction prompt.

  • previous_steps

    array

    Previous steps applied before testing this one. json steps may pass a transform template as pattern or provide jsonConditions.

    Array items

    • [item]

      object

      Nested fields

      • method

        string (xPath, xPath_extract, json, regex, gpt)

        Previous step method

        Allowed values: xPath, xPath_extract, json, regex, gpt

      • pattern

        string

        Previous step pattern (null for json with jsonConditions)

      • jsonConditions

        string

        Optional stringified conditions for json step. Will be decoded/normalized.

  • use_cache

    boolean

    Use cached data if available (default: true)

Validate Monitoring Job

monitoring__validate_monitoring_jobMonitoring Automations

[STAGE 6: Validation] Run comprehensive checks: configuration, connectivity, tasks, extraction pipeline, production readiness. Levels: basic (config), full (config+connectivity+extraction), production (full + end-to-end + enable on success). Returns typed next_tools suggestions.

Parameters

  • job_id

    string

    Required

    Monitoring job ID to validate

  • validation_level

    string (basic, full, production)

    Required

    Validation depth. basic: config only. full: config + connectivity + extraction. production: full + end-to-end + enable on success.

    Allowed values: basic, full, production

  • fix_issues

    boolean

    Attempt to automatically fix common issues (default: false)

Last refreshed from MCP: Sep 22, 2025, 3:45 AM

Playbook ideas

Use these prompts as starting points. They combine multiple tools from this namespace with other MCP capabilities to deliver analyst-grade output.

Set up a competitor job board crawler

Use `monitoring__create_monitoring_job` with the target URL, then `monitoring__configure_extraction` and `monitoring__test_step` to refine parsing before production.

Forward download press releases and PDFs

Pair `monitoring__configure_forward_download` with `monitoring__preview_data` to capture attachments and feed them into downstream AI workflows.

Quality gate each revision

`monitoring__validate_monitoring_job` ensures your AI confirms transform samples and output schema so analysts can review the diff confidently.

Keep exploring

Hop back to the MCP catalog to combine these tools with monitoring, data, and reporting workflows.

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