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conduit_ingest

Send events to Conduit MCP data streams with automatic schema detection and evolution for real-time integration between services and AI agents.

Instructions

Send one or more events (JSON objects) to a stream. Schema is auto-detected and evolves.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
streamYesStream name
eventsYesEvent(s) to ingest

Implementation Reference

  • The request handler logic for 'conduit_ingest' which formats the payload and POSTs it to the Conduit API.
    case 'conduit_ingest': {
      const prefix = await getTenantPrefix();
      const events = Array.isArray(args!.events) ? args!.events : [args!.events];
      const data = await api(`/v1/${prefix}/${args!.stream}`, {
        method: 'POST',
        body: JSON.stringify(events.length === 1 ? events[0] : events),
      });
      return { content: [{ type: 'text', text: JSON.stringify(data, null, 2) }] };
    }
  • The tool definition and input schema registration for 'conduit_ingest'.
      name: 'conduit_ingest',
      description: 'Send one or more events (JSON objects) to a stream. Schema is auto-detected and evolves.',
      inputSchema: {
        type: 'object' as const,
        properties: {
          stream: { type: 'string', description: 'Stream name' },
          events: {
            oneOf: [
              { type: 'object', description: 'Single event' },
              { type: 'array', items: { type: 'object' }, description: 'Batch of events' },
            ],
            description: 'Event(s) to ingest',
          },
        },
        required: ['stream', 'events'],
      },
    },

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions schema auto-detection and evolution, which adds some behavioral context beyond basic ingestion. However, it lacks critical details like authentication requirements, rate limits, error handling, or whether this is a write operation (implied by 'Send' but not confirmed). For a tool with no annotations, this is insufficient.

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

Conciseness5/5

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

The description is a single, efficient sentence that front-loads the core purpose ('Send one or more events to a stream') and adds useful context ('Schema is auto-detected and evolves'). There is no wasted verbiage, and every part earns its place by clarifying the tool's behavior.

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

Completeness3/5

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

Given 2 parameters with full schema coverage and no output schema, the description is moderately complete. It covers the basic action and schema behavior but lacks details on usage guidelines, error cases, or integration with sibling tools. For a tool with no annotations and multiple siblings, it should provide more context to be fully helpful.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema fully documents the two parameters ('stream' and 'events'). The description adds no additional meaning about parameters beyond what the schema provides (e.g., format examples or constraints). Baseline score of 3 is appropriate as the schema handles parameter documentation adequately.

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

Purpose4/5

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

The description clearly states the action ('Send') and resource ('events to a stream'), with additional context about schema auto-detection and evolution. It distinguishes from siblings like 'conduit_list_events' or 'conduit_create_stream' by focusing on ingestion rather than listing or creation. However, it doesn't explicitly contrast with all siblings (e.g., 'conduit_backfill' might also involve sending events).

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention when to choose 'conduit_ingest' over 'conduit_backfill' for historical data or 'conduit_feedback' for corrections. The description implies usage for sending events but lacks explicit context or exclusions.

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