io.github.TsvetanG2/cognigy-ai-mcp-management-server

NPM · COGNIGY-AI-MCP-MANAGEMENT-SERVER · SCANNED AUG 3

MCP server for Cognigy.AI - 132 tools to build, configure & operate conversational AI agents

Available components

npm · cognigy-ai-mcp-management-server 66

+5 this week 66 66 Trust /100

Trust breakdown (6 categories)

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score →

Supply Chain Security86

No malware found by supply-chain analysis.Pass
Only part of the dependency tree could be resolved (94 of 98), so this covers what we could see, not the whole tree.Partial
No install/post-install scripts declared.Pass
Only part of the dependency tree could be resolved (94 of 98), so this covers what we could see, not the whole tree. View diagnostics → Partial

Provenance & Transparency45

Source repository is publicly reachable at the declared URL. View diagnostics → Pass
Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
Clear OSI-approved license (MIT).Pass
Actively maintained (last published 6 days ago).Pass
Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail

Schema Quality & AI Usability79

AI-judged instruction clarity (excellent).Pass
Context-footprint check failed: tool/resource definitions use about 14859 tokens (~107/item across 138 items; 138 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
Usage-examples check failed: none of the tools include examples. See how to fix → Fail

Stability & Change Management0

Stability not yet verified: not enough scan history yet (needs a 30-day window).Unverified

Tool Coverage100

100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
100% of tool parameters carry a description.Pass

Capabilities100

Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass

Unverified: 1 category

A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.

Install

Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.

npm · cognigy-ai-mcp-management-server

Claude Codex opencode OpenClaw Hermes Other

# add to Claude Code

claude mcp add tsvetang2-cognigy-ai-mcp-management-server -- npx -y cognigy-ai-mcp-management-server

# add to Codex CLI

codex mcp add tsvetang2-cognigy-ai-mcp-management-server -- npx -y cognigy-ai-mcp-management-server

// opencode.json

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "tsvetang2-cognigy-ai-mcp-management-server": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "cognigy-ai-mcp-management-server"
      ],
      "enabled": true
    }
  }
}

# add to OpenClaw

openclaw mcp add tsvetang2-cognigy-ai-mcp-management-server --command npx --arg -y --arg cognigy-ai-mcp-management-server

# ~/.hermes/config.yaml

mcp_servers:
  tsvetang2-cognigy-ai-mcp-management-server:
    command: "npx"
    args: ["-y", "cognigy-ai-mcp-management-server"]

// mcp.json

{
  "mcpServers": {
    "tsvetang2-cognigy-ai-mcp-management-server": {
      "command": "npx",
      "args": [
        "-y",
        "cognigy-ai-mcp-management-server"
      ]
    }
  }
}

Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

3 Aug 26 +38
- Known CVEs: unverified → partial ▲ security
- Stability: Stability not yet verified: not enough scan history yet (needs a 30-day window). security
- Tool coverage: unverified → 100 ▲ functional
- MCP protocol: unverified → pass ▲ functional
- Dependency health: unverified → partial ▲ functional
2 Aug 26 −26
- Known CVEs: partial → unverified ▼ security
- Malware scan: unverified → pass ▲ security
- Stability: Stability not yet verified: we do not have a sandbox capture of the MCP schema this version of the package serves yet. security
- Dependency health: partial → unverified ▼ functional
- Tool coverage: 100 → unverified ▼ functional
- Capabilities: pass → unverified ▼ functional
- First check of Schema quality: unverified functional
1 Aug 26 +18
- Provenance: unverified → fail ▼ security
- GHSA-frvp-7c67-39w9 no longer affects this package ▲ security
- Install scripts: unverified → pass ▲ security
- Known CVEs: unverified → partial ▲ security
- Maintenance: unverified → pass ▲ functional
- License: unverified → pass ▲ functional
- Dependency health: unverified → partial ▲ functional
- Licence: MIT functional
31 Jul 26 −5
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
28 Jul 26 −20
- Install scripts: pass → unverified ▼ security
- Known CVEs: fail → unverified ▼ security
- Provenance: fail → unverified ▼ security
- GHSA-frvp-7c67-39w9 no longer affects this package ▲ security
- Maintenance: pass → unverified ▼ functional
- Dependency health: partial → unverified ▼ functional
- License: pass → unverified ▼ functional
- Licence: MIT functional
27 Jul 26 61

First indexed and scored.

Show 2 earlier entries Hide earlier entries

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 3 Aug 2026 · Analysed npm/[email protected]

Provenance none

Ecosystem: npm · Outcome: none

Dependencies 94 packages

94 packages in the resolved dependency tree · 94 deprecated · 29 stale.

The dependency tree was only partially resolved, so these counts may be incomplete.

MCP tools — 138 exposed · ~14,859 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.

Tool Tokens

get_flow ~53

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.

Input Output Examples

Name	Type	Req	Description
flowId	string	yes	The flow ID to retrieve

No output schema declared.

No examples provided.

get_flow_settings ~57

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

Input Output Examples

Name	Type	Req	Description
flowId	string	yes	The flow ID to retrieve settings for

No output schema declared.

No examples provided.

get_function ~44

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

Input Output Examples

Name	Type	Req	Description
functionId	string	yes	The function ID to retrieve

No output schema declared.

No examples provided.

get_function_instance ~61

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

Input Output Examples

Name	Type	Req	Description
functionId	string	yes	The function ID
functionInstanceId	string	yes	The function instance ID to retrieve

No output schema declared.

No examples provided.

get_handover_provider ~50

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

Input Output Examples

Name	Type	Req	Description
providerId	string	yes	The handover provider ID to retrieve

No output schema declared.

No examples provided.

get_handover_service ~51

Gets detailed information about a specific Cognigy.AI handover service. Returns service type, configuration schema, and supported features.

Input Output Examples

Name	Type	Req	Description
serviceId	string	yes	The handover service ID to retrieve

No output schema declared.

No examples provided.

get_intent ~89

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.

Input Output Examples

Name	Type	Req	Description
flowId	string	yes	The flow ID containing the intent
intentId	string	yes	The intent ID to retrieve
localeId	string	—	Optional locale ID for localized content

No output schema declared.

No examples provided.

get_knowledge_chunk ~91

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.

Input Output Examples

Name	Type	Req	Description
chunkId	string	yes	The knowledge chunk ID to retrieve
knowledgeStoreId	string	yes	The knowledge store ID
sourceId	string	yes	The knowledge source ID containing the chunk

No output schema declared.

No examples provided.

get_knowledge_connector ~66

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

Input Output Examples

Name	Type	Req	Description
connectorId	string	yes	The knowledge connector ID to retrieve
knowledgeStoreId	string	yes	The knowledge store ID containing the connector

No output schema declared.

No examples provided.

get_knowledge_query_metrics ~116

Gets Cognigy.AI Knowledge AI query metrics. Returns aggregated knowledge search/RAG query counts for a project or entire organization.

Input Output Examples

Name	Type	Req	Description
endDate	string	—	End date for metrics (ISO 8601 format)
projectId	string	—	Project ID for project-level metrics. Omit for organization-wide metrics.
startDate	string	—	Start date for metrics (ISO 8601 format)
timezone	string	—	Timezone for aggregation (e.g., 'UTC', 'America/New_York')

No output schema declared.

No examples provided.

get_knowledge_source ~67

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

Input Output Examples

Name	Type	Req	Description
knowledgeStoreId	string	yes	The knowledge store ID containing the source
sourceId	string	yes	The knowledge source ID to retrieve

No output schema declared.

No examples provided.

get_knowledge_store ~51

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

Input Output Examples

Name	Type	Req	Description
knowledgeStoreId	string	yes	The knowledge store ID to retrieve

No output schema declared.

No examples provided.

get_latest_log_entries ~109

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

Input Output Examples

Name	Type	Req	Description
flowName	string	—	Filter logs by flow name
limit	integer	—	Maximum number of log entries to return (1-100, default 25)
projectId	string	yes	The project ID to retrieve logs from
type	array	—	Filter by log level(s): debug, info, warn, error

No output schema declared.

No examples provided.

get_llm ~53

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

Input Output Examples

Name	Type	Req	Description
largeLanguageModelId	string	yes	The LLM ID to retrieve

No output schema declared.

No examples provided.

get_nlu_connector ~56

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

Input Output Examples

Name	Type	Req	Description
nluConnectorId	string	yes	The NLU connector ID to retrieve

No output schema declared.

No examples provided.

get_node ~88

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.

Input Output Examples

Name	Type	Req	Description
flowId	string	yes	The flow ID containing the node
localeId	string	—	Optional locale ID for localized content
nodeId	string	yes	The node ID to retrieve

No output schema declared.

No examples provided.

get_node_descriptors ~74

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.

Input Output Examples

Name	Type	Req	Description
flowId	string	yes	The flow ID to get available node types for

No output schema declared.

No examples provided.

get_nodes ~89

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.

Input Output Examples

Name	Type	Req	Description
flowId	string	yes	The flow ID to list nodes from
limit	integer	—	Maximum number of nodes to return (1-100, default 25)

No output schema declared.

No examples provided.

get_package ~43

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

Input Output Examples

Name	Type	Req	Description
packageId	string	yes	The package ID to get details for

No output schema declared.

No examples provided.

get_playbook ~52

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

Input Output Examples

Name	Type	Req	Description
playbookId	string	yes	The playbook ID to retrieve

No output schema declared.

No examples provided.

get_playbook_run ~70

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.

Input Output Examples

Name	Type	Req	Description
playbookId	string	yes	The playbook ID
playbookRunId	string	yes	The playbook run ID to retrieve

No output schema declared.

No examples provided.

get_snapshot ~53

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

Input Output Examples

Name	Type	Req	Description
snapshotId	string	yes	The snapshot ID to retrieve

No output schema declared.

No examples provided.

get_snapshot_resources ~97

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.

Input Output Examples

Name	Type	Req	Description
limit	integer	—	Maximum number of resources to return (1-100, default 25)
resourceType	string	yes	Type of resources to list
snapshotId	string	yes	The snapshot ID to list resources from

No output schema declared.

No examples provided.

get_task ~70

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.

Input Output Examples

Name	Type	Req	Description
projectId	string	—	Optional project ID to scope the query
taskId	string	yes	The task ID to retrieve

No output schema declared.

No examples provided.

get_transcript ~100

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.

Input Output Examples

Name	Type	Req	Description
format	string	—	Output format: 'full' includes all metadata, 'compact' shows just the conversation flow
projectId	string	—	Optional project ID to scope the query
sessionId	string	yes	The session ID to get transcript for

No output schema declared.

No examples provided.

inject_context ~90

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.

Input Output Examples

Name	Type	Req	Description
context	object	yes	The context object to inject (key-value pairs)
sessionId	string	yes	The session ID to inject context into
userId	string	yes	The user ID for the session

No output schema declared.

No examples provided.

list_audit_events ~195

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

Input Output Examples

Name	Type	Req	Description
endDate	string	—	End date for audit events (ISO 8601 format)
eventType	string	—	Filter by event type (e.g., 'create', 'update', 'delete')
limit	number	—	Maximum number of events to return (default: 25, max: 100)
projectId	string	—	Filter audit events by project ID
resourceType	string	—	Filter by resource type (e.g., 'flow', 'intent', 'endpoint')
skip	number	—	Number of items to skip for pagination
startDate	string	—	Start date for audit events (ISO 8601 format)
userId	string	—	Filter audit events by user ID

No output schema declared.

No examples provided.

list_connections ~133

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.

Input Output Examples

Name	Type	Req	Description
filter	string	—	Filter connections by name
limit	number	—	Maximum number of connections to return (default: 25, max: 100)
projectId	string	—	Filter connections by project ID. Omit for all accessible connections.
resourceLevel	string	—	Scope: 'organisation' for global connections, 'project' for project-specific
skip	number	—	Number of items to skip for pagination

No output schema declared.

No examples provided.

list_contact_profiles ~99

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

Input Output Examples

Name	Type	Req	Description
filter	string	—	Filter profiles by contact ID or other fields
limit	number	—	Maximum number of profiles to return (default: 25, max: 100)
projectId	string	—	Filter contact profiles by project ID
skip	number	—	Number of items to skip for pagination

No output schema declared.

No examples provided.

list_endpoints ~86

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.

Input Output Examples

Name	Type	Req	Description
limit	integer	—	Maximum number of endpoints to return (1-100, default 25)
projectId	string	yes	The project ID to list endpoints from

No output schema declared.

No examples provided.

list_extensions ~96

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

Input Output Examples

Name	Type	Req	Description
filter	string	—	Filter extensions by name
limit	number	—	Maximum number of extensions to return (default: 25, max: 100)
projectId	string	—	Filter extensions by project ID
skip	number	—	Number of items to skip for pagination

No output schema declared.

No examples provided.

list_flows ~74

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

Input Output Examples

Name	Type	Req	Description
limit	integer	—	Maximum number of flows to return (1-100, default 25)
projectId	string	yes	The project ID to list flows from

No output schema declared.

No examples provided.

list_function_instances ~83

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

Input Output Examples

Name	Type	Req	Description
functionId	string	yes	The function ID to list instances for
limit	number	—	Maximum number of instances to return (default: 25, max: 100)
skip	number	—	Number of items to skip for pagination

No output schema declared.

No examples provided.

list_functions ~99

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

Input Output Examples

Name	Type	Req	Description
filter	string	—	Filter functions by name
limit	number	—	Maximum number of functions to return (default: 25, max: 100)
projectId	string	—	Filter functions by project ID
skip	number	—	Number of items to skip for pagination

No output schema declared.

No examples provided.

list_handover_providers ~93

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

Input Output Examples

Name	Type	Req	Description
limit	number	—	Maximum number of providers to return (default: 25, max: 100)
projectId	string	—	Filter handover providers by project ID
skip	number	—	Number of items to skip for pagination

No output schema declared.

No examples provided.

list_handover_services ~71

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

Input Output Examples

Name	Type	Req	Description
limit	number	—	Maximum number of services to return (default: 25, max: 100)
skip	number	—	Number of items to skip for pagination

No output schema declared.

No examples provided.

list_intents ~113

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.

Input Output Examples

Name	Type	Req	Description
flowId	string	yes	The flow ID to list intents from
includeChildren	boolean	—	Include child intents in the results
limit	integer	—	Maximum number of intents to return (1-100, default 25)
localeId	string	—	Optional locale ID for localized content

No output schema declared.

No examples provided.

list_knowledge_chunks ~120

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

Input Output Examples

Name	Type	Req	Description
filter	string	—	Filter chunks by text content
knowledgeStoreId	string	yes	The knowledge store ID to list chunks from
limit	number	—	Maximum number of chunks to return (default: 25, max: 100)
skip	number	—	Number of items to skip for pagination
sourceId	string	—	Filter chunks by source ID

No output schema declared.

No examples provided.

list_knowledge_connectors ~107

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

Input Output Examples

Name	Type	Req	Description
filter	string	—	Filter connectors by name
knowledgeStoreId	string	yes	The knowledge store ID to list connectors from
limit	number	—	Maximum number of connectors to return (default: 25, max: 100)
skip	number	—	Number of items to skip for pagination

No output schema declared.

No examples provided.

list_knowledge_sources ~113

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.

Input Output Examples

Name	Type	Req	Description
filter	string	—	Filter sources by name
knowledgeStoreId	string	yes	The knowledge store ID to list sources from
limit	number	—	Maximum number of sources to return (default: 25, max: 100)
skip	number	—	Number of items to skip for pagination

No output schema declared.

No examples provided.

list_knowledge_stores ~109

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.

Input Output Examples

Name	Type	Req	Description
filter	string	—	Filter knowledge stores by name
limit	number	—	Maximum number of stores to return (default: 25, max: 100)
projectId	string	—	Filter knowledge stores by project ID
skip	number	—	Number of items to skip for pagination

No output schema declared.

No examples provided.

list_llms ~152

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.

Input Output Examples

Name	Type	Req	Description
filter	string	—	Filter LLMs by name
limit	number	—	Maximum number of LLMs to return (default: 25, max: 100)
projectId	string	—	Filter LLMs by project ID. Omit for all accessible LLMs.
resourceLevel	string	—	Scope: 'organisation' for global LLMs, 'project' for project-specific
skip	number	—	Number of items to skip for pagination

No output schema declared.

No examples provided.

list_nlu_connectors ~113

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

Input Output Examples

Name	Type	Req	Description
filter	string	—	Filter NLU connectors by name
limit	number	—	Maximum number of NLU connectors to return (default: 25, max: 100)
projectId	string	—	Filter NLU connectors by project ID
skip	number	—	Number of items to skip for pagination

No output schema declared.

No examples provided.

list_packages ~83

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

Input Output Examples

Name	Type	Req	Description
limit	integer	—	Maximum number of packages to return (1-100, default 25)
projectId	string	—	Project ID to list packages for. If omitted, lists all accessible packages.

No output schema declared.

No examples provided.

list_playbook_runs ~78

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

Input Output Examples

Name	Type	Req	Description
limit	integer	—	Maximum number of runs to return (1-100, default 25)
playbookId	string	yes	The playbook ID to list runs for

No output schema declared.

No examples provided.

list_playbooks ~74

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

Input Output Examples

Name	Type	Req	Description
limit	integer	—	Maximum number of playbooks to return (1-100, default 25)
projectId	string	yes	The project ID to list playbooks from

No output schema declared.

No examples provided.

list_projects ~59

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

Input Output Examples

Name	Type	Req	Description
limit	integer	—	Maximum number of projects to return (1-100, default 25)

No output schema declared.

No examples provided.

list_sentences ~86

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

Input Output Examples

Name	Type	Req	Description
flowId	string	yes	The flow ID containing the intent
intentId	string	yes	The intent ID to list sentences for
limit	integer	—	Maximum number of sentences to return (1-100, default 25)

No output schema declared.

No examples provided.

list_snapshots ~78

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.

Input Output Examples

Name	Type	Req	Description
limit	integer	—	Maximum number of snapshots to return (1-100, default 25)
projectId	string	yes	The project ID to list snapshots from

No output schema declared.

No examples provided.

list_tasks ~74

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

Input Output Examples

Name	Type	Req	Description
limit	integer	—	Maximum number of tasks to return (1-100, default 25)
projectId	string	—	Optional project ID to filter tasks

No output schema declared.

No examples provided.

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Scoring key

80+ high trust
60–79 medium
below 60 low

How we score

Score history · last 30 days

27 Jul 3 Aug