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cognigy-ai-mcp-management-server

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
list_projectsA

Lists all Cognigy.AI projects accessible by your API key. Use this to discover available projects before working with flows, intents, or other resources.

list_flowsA

Lists all flows in a Cognigy.AI project. Flows are conversation logic containers. Use this to discover flows before reading or modifying them.

get_flowA

Gets detailed metadata about a specific Cognigy.AI flow. Returns flow configuration, locale info, and timestamps. Use this to inspect a flow before modifying it.

get_flow_settingsA

Gets the settings/configuration of a Cognigy.AI flow. Returns NLU settings, thresholds, and other flow-level configurations. Use this before updating flow settings.

get_latest_log_entriesA

Gets the latest execution log entries from a Cognigy.AI project. Use this for debugging flow execution, viewing errors, or monitoring agent behavior.

get_nodesA

Lists all nodes in a Cognigy.AI flow. Nodes are the building blocks of conversation logic (Say, Question, If, Code, etc.). Use this to explore flow structure before reading specific nodes or modifying the flow.

get_nodeA

Gets detailed configuration of a specific node in a Cognigy.AI flow. Returns the node's type, label, config fields, and settings. Use this to inspect node behavior before modifying it.

search_nodesA

Searches for nodes in a Cognigy.AI flow by text content. Finds nodes containing the search term in their configuration (messages, conditions, code, etc.). Use this to locate specific content within large flows.

get_node_descriptorsA

Gets all available node types (blueprints) that can be created in a Cognigy.AI flow. Returns node type definitions including their fields, appearance, and constraints. Use this to understand what nodes can be added to a flow.

list_intentsA

Lists all intents in a Cognigy.AI flow. Intents are the NLU triggers that match user utterances to flow logic. Use this to explore NLU configuration before training or modifying intents.

get_intentA

Gets detailed configuration of a specific intent in a Cognigy.AI flow. Returns the intent's conditions, rules, confirmation sentences, and settings. Use this to inspect NLU behavior before modifying.

list_endpointsA

Lists all endpoints in a Cognigy.AI project. Endpoints are channel connectors (Webchat, REST, Voice, etc.) that expose flows/agents to users. Use this to discover deployed channels.

get_endpointA

Gets detailed configuration of a specific Cognigy.AI endpoint. Returns channel settings, flow/agent binding, and runtime configuration. Use this to inspect endpoint behavior.

inject_contextA

Injects context data into a Cognigy.AI session. Context is shared state accessible by flow nodes. Use this to set user data, preferences, or state before/during conversations.

reset_contextA

Resets the context for a Cognigy.AI session, clearing all stored state. Use this to start a fresh conversation or clear user data during testing.

get_conversationsA

Gets conversations for specific contacts in a Cognigy.AI project. Returns conversation history including inputs, outputs, and metadata. Use this to analyze user interactions.

get_conversationA

Gets conversation details for a specific Cognigy.AI session. Returns all inputs/outputs, timestamps, and metadata for the session. Use this to analyze a complete conversation thread.

get_transcriptA

Assembles a human-readable transcript for a Cognigy.AI session. Shows the conversation flow between user and bot in chronological order. Use this for reviewing conversation quality or debugging.

list_snapshotsA

Lists all snapshots in a Cognigy.AI project. Snapshots are versioned backups of project configuration used for deployment and rollback. Use this to see available versions.

get_snapshotA

Gets detailed information about a specific Cognigy.AI snapshot. Returns name, description, hash, and packaging status. Use this to inspect a version before deployment.

get_snapshot_resourcesA

Lists resources (flows, locales, NLU connectors, LLMs) contained in a Cognigy.AI snapshot. Use this to inspect what a snapshot contains before restoring or to compare versions.

list_tasksA

Lists async tasks in Cognigy.AI. Tasks track long-running operations like snapshot creation, training, and imports. Use this to monitor background job status.

get_taskA

Gets detailed status of a specific Cognigy.AI async task. Returns progress, status, and failure reason if applicable. Use this to poll long-running operations to completion.

create_nodeA

Creates a new node in a Cognigy.AI flow. MUTATING: This modifies the flow. Use dryRun=true (default) to validate first. Nodes are the building blocks of conversation logic (Say, Question, If, Code, etc.).

update_nodeA

Updates an existing node in a Cognigy.AI flow. MUTATING: This modifies the node. Use dryRun=true (default) to validate first. Only provided fields are updated; others remain unchanged.

delete_nodeA

Deletes a node from a Cognigy.AI flow. MUTATING & DESTRUCTIVE: This permanently removes the node. Use dryRun=true (default) to validate first. Child nodes may also be affected.

move_nodeA

Moves a node to a new position in a Cognigy.AI flow. MUTATING: This reorganizes the flow structure. Use dryRun=true (default) to validate first. Moving nodes affects execution order.

generate_node_outputA

Uses Cognigy's generative AI to create content for Say nodes. Generates either plain text messages or rich Adaptive Cards based on a natural language prompt. Returns content you can use with create_node or update_node.

create_intentA

Creates a new intent in a Cognigy.AI flow for NLU recognition. MUTATING: This modifies the flow. Use dryRun=true (default) to validate first. After creating, use train_intents to train the NLU model.

update_intentA

Updates an existing intent in a Cognigy.AI flow. MUTATING: This modifies the intent. Use dryRun=true (default) to validate first. After updating, call train_intents to retrain the NLU model.

delete_intentA

Deletes an intent from a Cognigy.AI flow. MUTATING & DESTRUCTIVE: This permanently removes the intent and its example sentences. Use dryRun=true (default) to validate first. After deleting, call train_intents to retrain.

train_intentsA

Trains the NLU model for a Cognigy.AI flow. MUTATING: This triggers model training. Use dryRun=true (default) to validate first. Training is async - this tool polls until completion or timeout.

list_sentencesA

Lists example sentences (training data) for a Cognigy.AI NLU intent. Use this to review training data quality before training.

create_sentenceA

Creates a new example sentence for Cognigy.AI NLU intent training. MUTATING: This modifies the intent's training data. Use dryRun=true (default) to validate first. After creating, call train_intents to retrain.

generate_sentencesA

Uses Cognigy AI to generate example sentences for an intent. The generated sentences are NOT automatically added - use create_sentence to add them. Useful for quickly expanding NLU training data.

list_playbooksA

Lists all playbooks in a Cognigy.AI project. Playbooks are automated test scenarios with steps and assertions for testing conversational flows.

get_playbookA

Gets detailed Cognigy.AI playbook configuration including all steps and assertions. Use this to understand what a playbook tests before running it.

run_playbookA

Runs a Cognigy.AI playbook test scenario against a flow. MUTATING: This executes test assertions. Use dryRun=true (default) to validate first. Returns pass/fail results with assertion details.

list_playbook_runsA

Lists Cognigy.AI playbook run history showing pass/fail status, timestamps, and run metadata. Use this to review test results over time.

get_playbook_runA

Gets detailed results of a Cognigy.AI playbook run including step-by-step assertion outcomes. Use this to analyze test failures and debug conversation flows.

generate_nlu_scoresA

Scores a test utterance against a Cognigy.AI flow's trained NLU intents. Returns ranked intent matches with confidence scores. Use this to test NLU recognition before deployment.

score_utteranceA

Scores a test utterance against a Cognigy.AI flow's trained NLU intents. Returns the best matching intent with confidence score. Use this to quickly test if an utterance would be recognized correctly.

run_regressionA

Runs all Cognigy.AI playbooks in a project as a regression test suite. MUTATING: This executes tests. Use dryRun=true (default) to preview. Returns pass/fail summary with failing playbooks highlighted.

audit_nluA

Audits Cognigy.AI NLU quality for a flow. Identifies intents with too few training sentences, disabled intents, and optionally checks for overlapping intents. Use this before deployment to ensure NLU quality.

create_snapshotA

Creates a snapshot of a Cognigy.AI project. Snapshots capture the entire project configuration (flows, intents, endpoints, etc.) for backup or deployment. MUTATING: Set dryRun=false to create. Async operation - polls until complete.

delete_snapshotA

Deletes a snapshot from a Cognigy.AI project. DESTRUCTIVE & IRREVERSIBLE: The snapshot and all its data will be permanently removed. Use dryRun=true (default) to validate first. Async operation.

create_snapshot_download_linkA

Creates a temporary download link for a Cognigy.AI snapshot. The link can be used to download the snapshot as a file for backup or transfer to another environment. Links are time-limited.

restore_snapshotA

Restores a snapshot to its Cognigy.AI project, replacing the current configuration. DESTRUCTIVE: Current project state will be overwritten with the snapshot's state. Use dryRun=true (default) to validate first. Async operation.

package_snapshotA

Packages a Cognigy.AI snapshot for download or transfer. Creates a downloadable package from the snapshot. Use create_snapshot_download_link after packaging to get the download URL. MUTATING: Set dryRun=false to package. Async operation.

upload_snapshot_packageA

Uploads a snapshot package file to a Cognigy.AI project. Use this to restore a previously downloaded snapshot or transfer a snapshot between environments. MUTATING: Set dryRun=false to upload. Async operation.

list_packagesA

Lists packages in a Cognigy.AI project. Packages are portable bundles of resources (flows, intents, etc.) that can be transferred between projects or environments.

get_packageA

Gets detailed information about a Cognigy.AI package including its name, description, and contained resources.

create_packageA

Creates a package from selected resources in a Cognigy.AI project. Packages bundle flows, endpoints, and other resources for transfer between projects. MUTATING: Set dryRun=false to create. Async operation.

delete_packageA

Deletes a package from a Cognigy.AI project. DESTRUCTIVE & IRREVERSIBLE: The package will be permanently removed. Use dryRun=true (default) to validate first. Async operation.

merge_packageA

Merges a package into a Cognigy.AI project, importing selected resources. Use localeMapping to map package locales to project locales. KNOWN LIMITATION: in live testing (Cognigy 2026.20) every merge failed with 'Resource with id ... is not in the source', and the public API offers no way to list a package's resources; if this happens, import the package in the Cognigy.AI UI instead. MUTATING: Set dryRun=false to merge. Async operation.

upload_packageA

Uploads a package file to a Cognigy.AI project. Use this to import a previously downloaded package or transfer resources between environments. MUTATING: Set dryRun=false to upload. Async operation.

create_package_download_linkA

Creates a temporary download link for a Cognigy.AI package. The link can be used to download the package file for backup or transfer. Links are time-limited.

diff_snapshotsA

Compares two Cognigy.AI snapshots and shows what changed (added, removed, modified resources). Useful for reviewing changes before deployment or understanding what a snapshot update will affect.

promote_snapshotA

Promotes a Cognigy.AI snapshot for deployment by packaging it and generating a download link. Use this to prepare a snapshot for transfer to another environment. MUTATING: Set dryRun=false to package. Async operation.

clone_flowA

Clones a Cognigy.AI flow within the same project. Creates an exact copy of the flow including all nodes, intents, and configurations. The cloned flow gets an auto-generated name. MUTATING: Set dryRun=false to clone.

list_connectionsA

Lists Cognigy.AI connections (external service integrations like databases, APIs, etc.). Connections store credentials securely. Use this to find available connections for a project or organization.

get_connectionA

Gets detailed information about a specific Cognigy.AI connection. Returns connection metadata and schema. NOTE: Secret values are REDACTED for security - this tool only shows field names, not actual credentials.

create_connectionA

Creates a new Cognigy.AI connection for external service integration. Connections securely store credentials like API keys, passwords, and tokens. MUTATING: Set dryRun=false to create.

update_connectionA

Updates an existing Cognigy.AI connection. Use this to change connection name or update credential values. MUTATING: Set dryRun=false to update.

delete_connectionA

Deletes a Cognigy.AI connection. WARNING: This is destructive and cannot be undone. Flows using this connection will break. MUTATING: Set dryRun=false to delete.

list_llmsA

Lists Cognigy.AI large language model configurations. LLMs are used for generative AI features like Knowledge AI, AI Agents, and node output generation. Shows provider, model type, and connection info.

get_llmA

Gets detailed configuration of a specific Cognigy.AI large language model. Returns provider settings, model type, connection details, and fallback configuration.

create_llmA

Creates a new Cognigy.AI large language model configuration. LLMs power Knowledge AI, AI Agents, and generative features. Requires a connection with provider credentials. MUTATING: Set dryRun=false to create.

update_llmA

Updates an existing Cognigy.AI large language model configuration. Use this to change name, description, credentials, or provider settings. MUTATING: Set dryRun=false to update.

delete_llmA

Deletes a Cognigy.AI large language model configuration. WARNING: Features using this LLM will stop working. MUTATING: Set dryRun=false to delete.

clone_llmA

Clones a Cognigy.AI large language model configuration. Creates a copy with the same settings that can be modified independently. MUTATING: Set dryRun=false to clone.

test_llm_connectionA

Tests the connection to a Cognigy.AI large language model provider. Validates that the credentials are correct and the provider is reachable. Use this to verify LLM setup before using it in flows.

list_nlu_connectorsA

Lists Cognigy.AI NLU connectors. NLU connectors enable integration with external NLU services like Dialogflow, LUIS, Watson, or custom solutions for intent recognition.

get_nlu_connectorA

Gets detailed configuration of a specific Cognigy.AI NLU connector. Returns type, settings, and connection details for external NLU service integration.

create_nlu_connectorA

Creates a new Cognigy.AI NLU connector for external NLU service integration. Supports Dialogflow, LUIS, Watson, Alexa, Lex, and custom code connectors. MUTATING: Set dryRun=false to create.

update_nlu_connectorA

Updates an existing Cognigy.AI NLU connector. Use this to change name or update type-specific settings. MUTATING: Set dryRun=false to update.

delete_nlu_connectorA

Deletes a Cognigy.AI NLU connector. WARNING: Endpoints using this connector will lose NLU functionality. MUTATING: Set dryRun=false to delete.

list_knowledge_storesA

Lists Cognigy.AI Knowledge AI stores. Knowledge stores are containers for RAG (Retrieval-Augmented Generation) content used by AI Agents to answer questions from your data.

get_knowledge_storeA

Gets detailed configuration of a specific Cognigy.AI knowledge store. Returns store settings, language, embedding model, and source counts.

create_knowledge_storeA

Creates a new Cognigy.AI knowledge store for RAG content. Knowledge stores contain sources (documents) that AI Agents can search to answer questions. MUTATING: Set dryRun=false to create.

update_knowledge_storeA

Updates an existing Cognigy.AI knowledge store. Use this to change name or description. MUTATING: Set dryRun=false to update.

delete_knowledge_storeA

Deletes a Cognigy.AI knowledge store and ALL its sources and chunks. WARNING: This is destructive and cannot be undone. AI Agents using this store will lose access. MUTATING: Set dryRun=false to delete.

list_knowledge_sourcesA

Lists knowledge sources in a Cognigy.AI knowledge store. Sources are documents (PDFs, web pages, text files) that have been ingested and chunked for RAG retrieval.

get_knowledge_sourceA

Gets detailed information about a specific Cognigy.AI knowledge source. Returns source metadata, processing status, chunk count, and ingestion details.

create_knowledge_sourceA

Creates a new Cognigy.AI knowledge source for RAG content ingestion. Sources can be URLs, uploaded files, or manual text. Content is automatically chunked and embedded. MUTATING: Set dryRun=false to create.

update_knowledge_sourceA

Updates an existing Cognigy.AI knowledge source. Use this to change name or description. MUTATING: Set dryRun=false to update.

delete_knowledge_sourceA

Deletes a Cognigy.AI knowledge source and all its chunks. WARNING: This is destructive. The document content will no longer be searchable. MUTATING: Set dryRun=false to delete.

list_knowledge_chunksA

Lists knowledge chunks in a Cognigy.AI knowledge store. Chunks are the actual text segments used for RAG retrieval, created by splitting source documents.

get_knowledge_chunkA

Gets the full content of a specific Cognigy.AI knowledge chunk. Returns the complete text, metadata, and source information. Use this to inspect what content is being used in RAG searches.

create_knowledge_chunkA

Creates a new Cognigy.AI knowledge chunk manually. Use this to add specific text segments that should be searchable via RAG. The chunk will be embedded automatically. MUTATING: Set dryRun=false to create.

update_knowledge_chunkA

Updates an existing Cognigy.AI knowledge chunk. If text is changed, the chunk will be re-embedded. MUTATING: Set dryRun=false to update.

delete_knowledge_chunkA

Deletes a Cognigy.AI knowledge chunk. The content will no longer be searchable via RAG. MUTATING: Set dryRun=false to delete.

list_knowledge_connectorsA

Lists Cognigy.AI knowledge connectors for automated content ingestion. Connectors can pull content from external sources like SharePoint, Confluence, or custom APIs.

get_knowledge_connectorA

Gets detailed configuration of a specific Cognigy.AI knowledge connector. Returns connector type, schedule, connection settings, and run status.

create_knowledge_connectorA

Creates a new Cognigy.AI knowledge connector for automated content ingestion from external sources like SharePoint or Confluence. MUTATING: Set dryRun=false to create.

update_knowledge_connectorA

Updates an existing Cognigy.AI knowledge connector. Use this to change settings or name. MUTATING: Set dryRun=false to update.

delete_knowledge_connectorA

Deletes a Cognigy.AI knowledge connector. Stops automated content ingestion from the external source. MUTATING: Set dryRun=false to delete.

run_knowledge_connectorA

Triggers a Cognigy.AI knowledge connector to run immediately. Pulls content from the external source and creates/updates knowledge chunks. MUTATING: Set dryRun=false to run.

list_functionsB

Lists Cognigy.AI Functions. Functions are custom code modules that can be triggered to run computations, integrations, or scheduled jobs outside of flow execution.

get_functionA

Gets detailed configuration of a specific Cognigy.AI Function. Returns the function code, settings, and runtime configuration.

create_functionA

Creates a new Cognigy.AI Function. Functions are custom code modules for integrations, scheduled jobs, or computations. MUTATING: Set dryRun=false to create.

update_functionA

Updates an existing Cognigy.AI Function. Use this to change its name or code, or to enable/disable it. MUTATING: Set dryRun=false to update.

delete_functionA

Deletes a Cognigy.AI Function. WARNING: This is destructive. Flows calling this function will fail. MUTATING: Set dryRun=false to delete.

list_function_instancesA

Lists running and completed instances of a Cognigy.AI Function. Shows execution history, status, and results.

get_function_instanceA

Gets detailed information about a specific Cognigy.AI Function instance. Returns execution status, timing, input parameters, and output/error.

trigger_functionA

Triggers a Cognigy.AI Function to run immediately. Creates a new function instance that executes the function code. MUTATING: Set dryRun=false to trigger.

stop_function_instanceA

Stops a running Cognigy.AI Function instance. Use this to cancel a long-running or stuck function. MUTATING: Set dryRun=false to stop.

list_extensionsA

Lists Cognigy.AI Extensions. Extensions are custom node packages that add new capabilities to flows (e.g., integrations, custom actions).

get_extensionA

Gets detailed information about a specific Cognigy.AI Extension. Returns package info, available nodes, connections schemas, and settings.

delete_extensionA

Deletes a Cognigy.AI Extension. WARNING: Flows using nodes from this extension will break. MUTATING: Set dryRun=false to delete.

update_extensionA

Updates Cognigy.AI Extension settings like trusted code flag. Use this to enable/disable full Node.js API access. MUTATING: Set dryRun=false to update.

upload_extensionA

Uploads a new Cognigy.AI Extension from a URL. The extension package must be a .tar.gz file. This is an async operation that polls until complete. MUTATING: Set dryRun=false to upload.

update_extension_packageA

Updates a Cognigy.AI Extension with a new package version from a URL. Use this to upgrade an extension to a new version. MUTATING: Set dryRun=false to update.

list_contact_profilesB

Lists Cognigy.AI contact profiles. Contact profiles store user data across sessions (name, preferences, conversation history metadata).

get_contact_profileA

Gets detailed information about a specific Cognigy.AI contact profile. Returns stored user data, goals, and profile metadata.

create_contact_profileA

Creates a new Cognigy.AI contact profile. Contact profiles persist user data across sessions for personalization. MUTATING: Set dryRun=false to create.

update_contact_profileA

Updates an existing Cognigy.AI contact profile. Use this to modify stored user data or GDPR consent. MUTATING: Set dryRun=false to update.

delete_contact_profileA

Deletes a Cognigy.AI contact profile. WARNING: This permanently removes all stored user data for this profile. MUTATING: Set dryRun=false to delete.

remove_contact_idA

Removes a contact ID from a Cognigy.AI contact profile. Use this when a user identifier should no longer be associated with a profile. MUTATING: Set dryRun=false to remove.

merge_contact_profilesA

Merges the Cognigy.AI contact profile of a given contact ID into a target profile, combining their data and contact IDs. Use when the same user has multiple profiles. MUTATING: Set dryRun=false to merge.

unmerge_contact_profilesA

Splits a merged Cognigy.AI contact profile back into separate profiles. Use when profiles were incorrectly merged. MUTATING: Set dryRun=false to unmerge.

export_contact_profileA

Exports all data for a Cognigy.AI contact profile. Use this for GDPR data access requests. Returns all stored profile data in a portable format.

get_contact_profile_schemaA

Gets the contact profile schema for a Cognigy.AI project. The schema defines what custom fields can be stored in contact profiles.

set_contact_profile_schemaA

Adds or updates custom fields in the Cognigy.AI contact profile schema of a project. Built-in fields (firstname, email, ...) always exist; existing custom fields not listed are kept. MUTATING: Set dryRun=false to update.

get_conversation_metricsA

Gets Cognigy.AI conversation counter metrics for one month. Returns aggregated conversation counts for a project or the entire organization.

get_call_metricsA

Gets Cognigy.AI call counter metrics (Voice Gateway) for one month. Returns aggregated call counts for a project or the entire organization.

get_knowledge_query_metricsA

Gets Cognigy.AI Knowledge AI query counter metrics for one month. Returns aggregated knowledge query counts for a project or the entire organization.

update_analytics_recordA

Updates Cognigy.AI analytics records for a session. Use this to add custom tracking properties to conversation analytics. MUTATING: Set dryRun=false to update.

list_audit_eventsA

Lists Cognigy.AI audit events. Audit events track all changes made to resources (flows, intents, endpoints, etc.) by users. Useful for compliance and debugging.

get_audit_eventA

Gets detailed information about a specific Cognigy.AI audit event. Returns the full change details including before/after values.

list_handover_providersA

Lists Cognigy.AI handover providers. Handover providers enable live agent escalation (e.g., Salesforce, Genesys, RingCentral).

get_handover_providerA

Gets detailed information about a specific Cognigy.AI handover provider. Returns provider type, configuration, and connection settings.

create_handover_providerA

Creates a new Cognigy.AI handover provider for live agent escalation, based on one of the services from list_handover_services. The provider starts with the service's default properties; change them with update_handover_provider. MUTATING: Set dryRun=false to create.

update_handover_providerA

Updates an existing Cognigy.AI handover provider. Use this to rename it or change its properties. MUTATING: Set dryRun=false to update.

delete_handover_providerA

Deletes a Cognigy.AI handover provider. WARNING: Endpoints using this provider will no longer be able to escalate to live agents. MUTATING: Set dryRun=false to delete.

list_handover_servicesB

Lists available Cognigy.AI handover services. Handover services are the supported integrations for live agent escalation.

get_handover_serviceA

Gets detailed information about a specific Cognigy.AI handover service (accepts the service ID or name). Returns its version, service URL, and properties.

search_resourcesA

Searches across all Cognigy.AI resources in the organization. Finds flows, intents, endpoints, functions, playbooks, and more by name or content. Powerful for discovering resources across projects.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.5/5.0

Scored across 138 tools

Disambiguation3/5

Most tools have distinct purposes, but several pairs overlap noticeably (e.g., score_utterance vs generate_nlu_scores both score utterances against NLU intents; create_package, package_snapshot, and promote_snapshot all package resources). Descriptions help, but with 138 tools the agent can still misselect among similar-sounding operations.

Naming Consistency5/5

Every tool follows a consistent snake_case verb_noun pattern (e.g., list_flows, get_node, create_intent, delete_knowledge_store). Minor variations like get_nodes vs get_node are natural, and no mixed conventions appear.

Tool Count1/5

138 tools far exceeds reasonable bounds for an agent-facing server, even given Cognigy.AI's broad platform. This extreme count creates a high cognitive load and increases selection errors, matching the rubric's 50+ tools criterion for an extreme mismatch.

Completeness3/5

Coverage is broad across many resources (NLU, knowledge, contacts, snapshots, packages, functions, LLMs), but notable gaps exist: no create_flow/update_flow/delete_flow, no create_endpoint/update_endpoint/delete_endpoint, and no update_flow_settings. These missing core CRUD operations for central resources limit end-to-end management workflows.

Maintenance

ActivityActive
ResponsivenessNo issues