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Execute Connector Operation

execute_connector_operation

Execute a specific operation on a connected connector.

Use get_connector_capabilities to discover available operations. Operations include read/write actions specific to each connector.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoOperation-specific input data
operationYesOperation name (e.g., 'publish', 'read_posts', 'campaigns.list')
connectorIdYesConnector ID
idempotencyKeyNoIdempotency key to prevent duplicate operations (optional)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=false and openWorldHint=true. The description adds that operations 'include read/write actions specific to each connector,' providing extra context about the tool's behavior beyond the annotations. It does not contradict annotations and gives useful information about the scope of operations, though it remains somewhat general given the open-world nature.

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 two sentences with no filler. The first sentence states the core purpose, and the second provides a critical usage pointer. Every word earns its place, and the structure is front-loaded and scannable.

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

Completeness4/5

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

Given the tool's generic, open-world nature, the description succinctly covers the key usage pattern (discover via get_connector_capabilities, then execute). The schema covers parameter semantics, and no output schema exists, so return values need not be explained. It is complete enough for selecting and invoking this dynamic tool, though it could mention error-handling or validation behavior.

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?

The input schema has 100% description coverage: connectorId, operation, data, and idempotencyKey are all described, including example operation names. The description adds no further parameter-specific details, but the schema already carries the full semantic load, so a baseline score of 3 is appropriate.

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 the tool's function: 'Execute a specific operation on a connected connector.' This identifies the verb (execute), the resource (operation on a connector), and distinguishes it from sibling tools like get_connector_capabilities (discovery) and connect_connector (connecting). The second sentence clarifies that operations are connector-specific, further aiding selection.

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?

The description explicitly directs users to get_connector_capabilities to discover available operations, providing a clear prerequisite and alternative. It implies that this tool is for executing operations once capabilities are known, but does not explicitly state when not to use it or mention other alternatives. This is clear context with a named alternative, but lacks an explicit exclusion.

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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TDQS

B3/5.0
Disambiguation2/5

With 148 tools, there is significant overlap. For example, generate_content, publish_ai, generate_post_bundle, and request_project_content all generate content; get_analytics, get_unified_analytics, get_post_analytics, get_ad_performance, and get_unified_ad_report all fetch performance metrics; and list_inbox vs list_conversations blur comment and conversation management. Descriptions help, but boundaries between tools are often unclear.

Naming Consistency3/5

Most tools follow a verb_noun pattern (e.g., list_teams, create_goal, delete_post), but there are notable deviations: create_library_item vs save_to_library, publish_content vs publish_ai, schedule_content vs schedule_content_advanced, and connect_platform vs connect_connector. Mixed prefixes like 'autopilot_', 'check_', and 'get_' are fine, but overlapping verbs and a hyphen in 'connect_linkedin-page' reduce consistency.

Tool Count1/5

148 tools is extreme for any server. Even for a broad social media management platform, this is far beyond what an agent can effectively navigate. The count is unwieldy and suggests the surface should be split into multiple focused servers (publishing, analytics, connectors, workflows, etc.).

Completeness3/5

The core social publishing workflow is well covered (create, schedule, publish, edit, delete, retry), and there are extensive features for analytics, workflows, connectors, and AI agents. However, some resources have CRUD gaps: no update/delete for brand voices, no delete_project, no update/delete for Product Hunt goals, and no explicit get_workflow. These are workable but notable omissions.

Resources