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Prisme.ai MCP Plugin

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by prismeai

search_events

Read-only

Search for events in a Prisme.ai workspace using Elasticsearch DSL queries. Filter by event type, automation, correlation ID, or other fields to find specific events.

Instructions

Search for events in Prisme.ai workspace using Elasticsearch DSL.

EVENT STRUCTURE:
Events contain the following key fields:
- @timestamp: Event timestamp (ISO 8601 format) - USE THIS FOR SORTING, NOT "timestamp"
- id: Unique event ID
- type: Event type (e.g., "runtime.automations.executed", "workspaces.pages.updated", "error")
- source: Metadata object containing:
  - correlationId: Groups all events from a single API request/operation
  - userId: User who triggered the event
  - sessionId: User session identifier
  - workspaceId: Workspace identifier
  - automationSlug: Automation name (for automation-related events)
  - http: HTTP request details (method, path, hostname, ip)
  - host: Service information (replica, service name)
- payload: Event-specific data (varies by event type)
- createdAt: Creation timestamp

COMMON QUERIES:
- Find all events for a specific request: {"bool": {"filter": [{"term": {"source.correlationId": "uuid-here"}}]}}
- Find automation executions: {"bool": {"filter": [{"term": {"type": "runtime.automations.executed"}}]}}
- Find events for specific automation: {"bool": {"filter": [{"term": {"source.automationSlug": "automation-name"}}]}}
- Find errors: {"bool": {"filter": [{"term": {"type": "error"}}]}}
- Exclude specific correlationId: {"bool": {"must_not": [{"term": {"source.correlationId": "uuid-here"}}]}}

SORTING:
- Always use "@timestamp" field for time-based sorting: [{"@timestamp": {"order": "desc"}}]
- DO NOT use "timestamp" as it's not mapped in the index

COMMON EVENT TYPES:
- runtime.automations.executed
- runtime.interactions.triggered
- runtime.dsul.updated
- workspaces.automations.created/updated/deleted
- workspaces.pages.created/updated/deleted
- error

ADDITIONAL INFO:
- SearchError are probably caused by your own previous failed attempt to create filters. This is usually not the event the user ask for. Keep searching for the events before the SearchError ones.
- Always use "source" to filter only the necessary fields. Only include the informations that are relevant to the user's request. Ignore durations, timestamps, IP adress if not asked for.

Supports full Elasticsearch DSL query syntax including aggregations, sorting, and pagination.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aggsNoElasticsearch aggregations to execute on the results (e.g., count by type, group by correlationId)
pageNoPage number (1-indexed)
sortNoElasticsearch sort criteria. IMPORTANT: Use "@timestamp" not "timestamp" for time-based sorting. Example: [{"@timestamp": {"order": "desc"}}]
limitNoPage size (number of documents to return, default varies by API)
queryYesElasticsearch DSL query object (e.g., {"match_all": {}} or {"bool": {"filter": [{"term": {"type": "event_name"}}]}})
sourceNoFields to include in the response. Omit to get all fields. Example: ["correlationId", "@timestamp", "type", "source.automationSlug", "payload"]
environmentNoOptional environment name (from PRISME_ENVIRONMENTS) to use specific API URL and workspace
workspaceIdNoAlternative: direct workspace ID (use workspaceName instead when possible)
workspaceNameYesWorkspace name that resolves to ID via PRISME_WORKSPACES or PRISME_ENVIRONMENTS mapping
track_total_hitsNoGet real total count instead of capped at 10000 (may impact performance)
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true; description adds valuable context such as the need to use @timestamp over timestamp and the meaning of SearchError events, enhancing transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with sections (EVENT STRUCTURE, COMMON QUERIES, etc.), front-loaded with purpose. Slightly long but justified for the complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, the description explains event structure and covers common use cases, parameter usage, and potential issues, making it fully contextually complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions, yet the description adds extra meaning with examples and common queries, going beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it searches for events in a Prisme.ai workspace using Elasticsearch DSL. It provides specific verb-resource and is well-distinguished from sibling tools like search_workspaces or ai_knowledge_query.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides extensive usage guidance including common queries, sorting tips, and handling of SearchError events. Lacks explicit 'when not to use' but given distinct purpose, it is sufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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