io.github.TsvetanG2/cognigy-ai-mcp-management-server
NPM · COGNIGY-AI-MCP-MANAGEMENT-SERVER · SCANNED OCT 2
MCP server for Cognigy.AI - 132 tools to build, configure & operate conversational AI agents
Available components
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 → Why this is hard to score →
Supply Chain Security89
- No malware found by supply-chain analysis.Pass
- CVE check failed: a known high-severity CVE affects axios 1.18.1, reached via @cognigy/rest-api-client > axios. A fixed version is available. View diagnostics → Fail
- No install/post-install scripts declared.Pass
- 61 of 137 dependencies flagged as unhealthy (2 deprecated). View diagnostics → Partial
Provenance & Transparency48
- 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 67 days ago).Pass
- Publishes a security disclosure policy (SECURITY.md).Pass
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 Management80
- Stability observed for 24 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
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
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- All 18 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation.Pass
- An AI judge read all 138 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
How do I install the io.github.TsvetanG2/cognigy-ai-mcp-management-server server?
io.github.TsvetanG2/cognigy-ai-mcp-management-server runs locally as an npm package, launched with npx -y cognigy-ai-mcp-management-server. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
npm · cognigy-ai-mcp-management-server
claude mcp add tsvetang2-cognigy-ai-mcp-management-server -- npx -y cognigy-ai-mcp-management-server
{
"mcpServers": {
"tsvetang2-cognigy-ai-mcp-management-server": {
"command": "npx",
"args": [
"-y",
"cognigy-ai-mcp-management-server"
]
}
}
} {
"servers": {
"tsvetang2-cognigy-ai-mcp-management-server": {
"command": "npx",
"args": [
"-y",
"cognigy-ai-mcp-management-server"
]
}
}
} codex mcp add tsvetang2-cognigy-ai-mcp-management-server -- npx -y cognigy-ai-mcp-management-server
{
"$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
}
}
} openclaw mcp add tsvetang2-cognigy-ai-mcp-management-server --command npx --arg -y --arg cognigy-ai-mcp-management-server
mcp_servers:
tsvetang2-cognigy-ai-mcp-management-server:
command: "npx"
args: ["-y", "cognigy-ai-mcp-management-server"] {
"McpServers": {
"tsvetang2-cognigy-ai-mcp-management-server": {
"Transport": "stdio",
"Command": "npx",
"Arguments": [
"-y",
"cognigy-ai-mcp-management-server"
]
}
}
} assistant mcp add tsvetang2-cognigy-ai-mcp-management-server -t stdio -c npx -a -y cognigy-ai-mcp-management-server
{
"mcpServers": {
"tsvetang2-cognigy-ai-mcp-management-server": {
"command": "npx",
"args": [
"-y",
"cognigy-ai-mcp-management-server"
]
}
}
} 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.
- 2 Oct 26 −3
- Stability: pass → 0.80 functional
- 1 Oct 26 +1
- CVE-2026-101908 affects this package: high ▼ security
- CVE-2026-101909 affects this package: high ▼ security
- CVE-2026-101901 affects this package: high ▼ security
- CVE-2026-101902 affects this package: high ▼ security
- CVE-2026-101900 affects this package: high ▼ security
- CVE-2026-101905 affects this package: high ▼ security
- CVE-2026-101899 affects this package: high ▼ security
- CVE-2026-101904 affects this package: high ▼ security
- CVE-2026-101906 affects this package: high ▼ security
- CVE-2026-101898 affects this package: high ▼ security
- CVE-2026-101907 affects this package: high ▼ security
- CVE-2026-101903 affects this package: high ▼ security
- Stability: 0.97 → pass security
- 29 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 90 to 93. That category is still filling its 30-day observation window: 27 days of observed history at the previous scan, 28 at this one. The score rises as the window fills, whether or not the server changes.
- 28 Sept 26 −2
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 26 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 80 to 83. That category is still filling its 30-day observation window: 24 days of observed history at the previous scan, 25 at this one. The score rises as the window fills, whether or not the server changes.
- 25 Sept 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 24 Sept 26 −3
- Stability: pass → 0.77 functional
- 23 Sept 26 0
- Stability: 0.97 → pass security
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 2 Oct 2026 · Analysed npm/cognigy-ai-mcp-management-server@0.1.4
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | npm |
Background: How many MCP packages publish verified provenance →
Vulnerabilities 14 findings
| ID | CVE | Severity | Vector | Fix available |
|---|---|---|---|---|
| GHSA-3pq3-5fj3-cg6v | CVE-2026-101898 | high | yes | |
| GHSA-44g4-m2mj-wpvx | CVE-2026-101899 | medium | yes | |
| GHSA-4hqw-qxg8-jxx2 | CVE-2026-101900 | medium | yes | |
| GHSA-542g-h47m-68v8 | CVE-2026-101901 | high | yes | |
| GHSA-9fr6-4gfg-395g | CVE-2026-101902 | medium | yes | |
| GHSA-c29m-xwm3-cm6r | CVE-2026-101903 | high | yes | |
| GHSA-j8rh-479h-cp32 | CVE-2026-101904 | medium | yes | |
| GHSA-m8m8-qj5v-23w3 | CVE-2026-101905 | high | yes | |
| GHSA-mghh-pgcx-3jjj | CVE-2026-101906 | high | yes | |
| GHSA-r4gj-5m52-g5wh | CVE-2026-101907 | high | yes | |
| GHSA-vh66-26gq-q6x8 | CVE-2026-101908 | medium | yes | |
| GHSA-x97p-jq2g-jp4f | CVE-2026-101909 | high | yes | |
| GHSA-hmw2-7cc7-3qxx | CVE-2026-12143 | high | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:N | yes |
| GHSA-w5hq-g745-h8pq | CVE-2026-41907 | high | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:N | yes |
Background: What a vulnerability scan can and cannot prove →
Dependencies 137 packages
| Packages resolved | 137 |
|---|---|
| Deprecated | 2 |
| Stale | 58 |
| No linked repository | 2 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
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. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
audit_nlu ~124
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.
| Name | Type | Req | Description |
|---|---|---|---|
| checkOverlap | boolean | – | If true, tests for overlapping intents using NLU scoring (slower) |
| flowId | string | yes | The flow ID to audit |
| minSentences | integer | – | Minimum recommended sentences per intent (default 5) |
| projectId | string | – | Required if checkOverlap=true - project ID for NLU scoring |
No output schema declared.
No examples provided.
clone_flow ~92
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.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without cloning. Set to false to actually clone. |
| flowId | string | yes | The flow ID to clone |
No output schema declared.
No examples provided.
clone_llm ~83
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.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without cloning. Set to false to actually clone. |
| largeLanguageModelId | string | yes | The LLM ID to clone |
No output schema declared.
No examples provided.
create_connection ~150
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.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without creating. Set to false to actually create. |
| fields | object | – | Connection field values as key-value pairs (e.g., { apiKey: '...', baseUrl: '...' }) |
| name | string | yes | Name for the connection |
| projectId | string | yes | The project ID to create the connection in |
| type | string | yes | Connection type (from extension schema, e.g., 'http-basic-auth', 'api-key', etc.) |
No output schema declared.
No examples provided.
create_contact_profile ~123
Creates a new Cognigy.AI contact profile. Contact profiles persist user data across sessions for personalization. MUTATING: Set dryRun=false to create.
| Name | Type | Req | Description |
|---|---|---|---|
| acceptedGDPR | boolean | – | Whether the user has accepted GDPR consent |
| contactId | string | yes | The unique contact identifier for this profile |
| dryRun | boolean | – | If true (default), validates without creating. Set to false to actually create. |
| profile | object | – | Profile data to store (custom fields) |
| projectId | string | yes | The project ID to create the profile in |
No output schema declared.
No examples provided.
create_function ~139
Creates a new Cognigy.AI Function. Functions are custom code modules for integrations, scheduled jobs, or computations. MUTATING: Set dryRun=false to create.
| Name | Type | Req | Description |
|---|---|---|---|
| code | string | – | The function code (JavaScript/TypeScript) |
| description | string | – | Description of the function's purpose |
| dryRun | boolean | – | If true (default), validates without creating. Set to false to actually create. |
| name | string | yes | Name for the function |
| parameters | object | – | Function parameters schema |
| projectId | string | yes | The project ID to create the function in |
| type | string | – | Function type |
No output schema declared.
No examples provided.
create_handover_provider ~152
Creates a new Cognigy.AI handover provider for live agent escalation. Configure providers like Salesforce, Genesys, or RingCentral. MUTATING: Set dryRun=false to create.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without creating. Set to false to actually create. |
| enabled | boolean | – | Whether the provider is enabled |
| name | string | yes | Name for the handover provider |
| projectId | string | yes | The project ID to create the handover provider in |
| settings | object | – | Provider-specific configuration settings |
| type | string | yes | Provider type (e.g., 'salesforce', 'genesys', 'ringcentral', 'custom') |
No output schema declared.
No examples provided.
create_intent ~212
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.
| Name | Type | Req | Description |
|---|---|---|---|
| condition | string | – | CognigyScript condition for additional matching constraints |
| confirmationSentences | array | – | Sentences used for intent confirmation |
| description | string | – | Human-readable description of what this intent recognizes |
| dryRun | boolean | – | If true (default), validates without creating. Set to false to actually create. |
| exampleSentences | array | – | Initial training sentences for the intent |
| flowId | string | yes | The flow ID where the intent will be created |
| isDisabled | boolean | – | Whether the intent is disabled (won't match) |
| name | string | yes | Intent name (unique within the flow) |
| rules | array | – | Additional rule patterns for matching |
| tags | array | – | Tags for organizing intents |
No output schema declared.
No examples provided.
create_knowledge_chunk ~146
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.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without creating. Set to false to actually create. |
| knowledgeStoreId | string | yes | The knowledge store ID to create the chunk in |
| metadata | object | – | Custom metadata for the chunk |
| sourceId | string | yes | The source ID to associate the chunk with |
| text | string | yes | The text content of the chunk |
| title | string | – | Title for the chunk |
No output schema declared.
No examples provided.
create_knowledge_connector ~153
Creates a new Cognigy.AI knowledge connector for automated content ingestion from external sources like SharePoint or Confluence. MUTATING: Set dryRun=false to create.
| Name | Type | Req | Description |
|---|---|---|---|
| connectionId | string | – | Connection ID for authentication |
| dryRun | boolean | – | If true (default), validates without creating. Set to false to actually create. |
| knowledgeStoreId | string | yes | The knowledge store ID to create the connector in |
| name | string | yes | Name for the connector |
| schedule | string | – | Cron expression for scheduled runs |
| settings | object | – | Type-specific connector settings |
| type | string | yes | Connector type (e.g., 'sharepoint', 'confluence', 'custom') |
No output schema declared.
No examples provided.
create_knowledge_source ~193
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.
| Name | Type | Req | Description |
|---|---|---|---|
| description | string | – | Description of the source content |
| dryRun | boolean | – | If true (default), validates without creating. Set to false to actually create. |
| knowledgeStoreId | string | yes | The knowledge store ID to create the source in |
| metadata | object | – | Custom metadata to attach to all chunks from this source |
| name | string | yes | Name for the knowledge source |
| text | string | – | Text content to ingest (for type 'manual') |
| type | string | – | Source type: 'manual' for text input, 'url' for web page |
| url | string | – | URL to ingest (required if type is 'url') |
No output schema declared.
No examples provided.
create_knowledge_store ~182
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.
| Name | Type | Req | Description |
|---|---|---|---|
| chunkOverlap | number | – | Overlap between chunks in characters |
| chunkSize | number | – | Size of text chunks in characters |
| description | string | – | Description of the knowledge store's purpose |
| dryRun | boolean | – | If true (default), validates without creating. Set to false to actually create. |
| embeddingModel | string | – | The embedding model to use for vectorization |
| language | string | – | Primary language for the knowledge store (e.g., 'en', 'de') |
| name | string | yes | Name for the knowledge store |
| projectId | string | yes | The project ID to create the knowledge store in |
No output schema declared.
No examples provided.
create_llm ~257
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.
| Name | Type | Req | Description |
|---|---|---|---|
| connectionId | string | yes | The connection ID containing the provider credentials |
| description | string | – | Description of the LLM's purpose |
| dryRun | boolean | – | If true (default), validates without creating. Set to false to actually create. |
| isDefault | boolean | – | Set as the default LLM for the project |
| modelGroup | string | – | Model group: 'chat' for conversational, 'completion' for text generation, 'embedding' for embeddings |
| modelType | string | yes | The model type (e.g., 'gpt-4o', 'claude-3-opus-20240229', 'gemini-2.0-flash') |
| name | string | yes | Name for the LLM configuration |
| projectId | string | yes | The project ID to create the LLM in |
| provider | string | yes | The LLM provider |
| providerConfig | object | – | Provider-specific configuration (e.g., resourceName, deploymentName for Azure) |
No output schema declared.
No examples provided.
create_nlu_connector ~136
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.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without creating. Set to false to actually create. |
| name | string | yes | Name for the NLU connector |
| projectId | string | yes | The project ID to create the NLU connector in |
| settings | object | – | Type-specific settings for the NLU connector |
| type | string | yes | The NLU connector type |
No output schema declared.
No examples provided.
create_node ~287
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.).
| Name | Type | Req | Description |
|---|---|---|---|
| comment | string | – | Developer comment/note for this node |
| config | object | – | Node-specific configuration object. Structure depends on node type. |
| dryRun | boolean | – | If true (default), validates the operation without creating the node. Set to false to actually create. |
| extension | string | – | Extension ID if this is a custom extension node |
| flowId | string | yes | The flow ID where the node will be created |
| label | string | – | Display label for the node in the flow editor |
| mode | string | – | How to position the new node relative to target: append (after), prepend (before), appendChild/prependChild (as child), insertChildAt (at position), insertAfter, insertBefore |
| position | integer | – | Position index when using insertChildAt mode |
| targetNodeId | string | yes | The ID of the target node relative to which this node will be positioned |
| type | string | yes | Node type (e.g., 'say', 'question', 'if', 'code', 'executeFlow'). Use get_node_descriptors to list available types. |
No output schema declared.
No examples provided.
create_package ~182
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.
| Name | Type | Req | Description |
|---|---|---|---|
| description | string | – | Optional description of the package |
| dryRun | boolean | – | If true (default), validates without creating. Set to false to actually create. |
| name | string | yes | Name for the package |
| pollIntervalMs | integer | – | How often to check task status (1-10 seconds, default 3) |
| projectId | string | yes | The project ID to create the package in |
| resourceIds | array | yes | Array of resource IDs to include in the package (flows, endpoints, etc.) |
| timeoutMs | integer | – | Maximum time to wait for package creation (5-600 seconds, default 120) |
No output schema declared.
No examples provided.
create_package_download_link ~61
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.
| Name | Type | Req | Description |
|---|---|---|---|
| packageId | string | yes | The package ID to create a download link for |
No output schema declared.
No examples provided.
create_sentence ~134
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.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without creating. Set to false to actually create. |
| flowId | string | yes | The flow ID containing the intent |
| intentId | string | yes | The intent ID to add the sentence to |
| localeId | string | yes | The locale ID for this sentence |
| text | string | yes | The example sentence text |
No output schema declared.
No examples provided.
create_snapshot ~193
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.
| Name | Type | Req | Description |
|---|---|---|---|
| description | string | – | Optional description of what this snapshot contains or why it was created |
| dryRun | boolean | – | If true (default), validates without creating. Set to false to actually create the snapshot. |
| name | string | yes | Name for the snapshot (e.g., 'v1.0.0', 'pre-release-backup') |
| pollIntervalMs | integer | – | How often to check task status (1-10 seconds, default 3) |
| projectId | string | yes | The project ID to create a snapshot of |
| timeoutMs | integer | – | Maximum time to wait for snapshot creation (5-600 seconds, default 120) |
No output schema declared.
No examples provided.
create_snapshot_download_link ~66
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.
| Name | Type | Req | Description |
|---|---|---|---|
| snapshotId | string | yes | The snapshot ID to create a download link for |
No output schema declared.
No examples provided.
delete_connection ~80
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.
| Name | Type | Req | Description |
|---|---|---|---|
| connectionId | string | yes | The connection ID to delete |
| dryRun | boolean | – | If true (default), validates without deleting. Set to false to actually delete. |
No output schema declared.
No examples provided.
delete_contact_profile ~78
Deletes a Cognigy.AI contact profile. WARNING: This permanently removes all stored user data for this profile. MUTATING: Set dryRun=false to delete.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without deleting. Set to false to actually delete. |
| profileId | string | yes | The contact profile ID to delete |
No output schema declared.
No examples provided.
delete_extension ~74
Deletes a Cognigy.AI Extension. WARNING: Flows using nodes from this extension will break. MUTATING: Set dryRun=false to delete.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without deleting. Set to false to actually delete. |
| extensionId | string | yes | The extension ID to delete |
No output schema declared.
No examples provided.
delete_function ~76
Deletes a Cognigy.AI Function. WARNING: This is destructive. Flows calling this function will fail. MUTATING: Set dryRun=false to delete.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without deleting. Set to false to actually delete. |
| functionId | string | yes | The function ID to delete |
No output schema declared.
No examples provided.
delete_handover_provider ~87
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.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without deleting. Set to false to actually delete. |
| providerId | string | yes | The handover provider ID to delete |
No output schema declared.
No examples provided.
delete_intent ~119
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.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without deleting. Set to false to actually delete. WARNING: Deletion cannot be undone. |
| flowId | string | yes | The flow ID containing the intent |
| intentId | string | yes | The ID of the intent to delete |
No output schema declared.
No examples provided.
delete_knowledge_chunk ~105
Deletes a Cognigy.AI knowledge chunk. The content will no longer be searchable via RAG. MUTATING: Set dryRun=false to delete.
| Name | Type | Req | Description |
|---|---|---|---|
| chunkId | string | yes | The knowledge chunk ID to delete |
| dryRun | boolean | – | If true (default), validates without deleting. Set to false to actually delete. |
| knowledgeStoreId | string | yes | The knowledge store ID |
| sourceId | string | yes | The knowledge source ID containing the chunk |
No output schema declared.
No examples provided.
delete_knowledge_connector ~91
Deletes a Cognigy.AI knowledge connector. Stops automated content ingestion from the external source. MUTATING: Set dryRun=false to delete.
| Name | Type | Req | Description |
|---|---|---|---|
| connectorId | string | yes | The knowledge connector ID to delete |
| dryRun | boolean | – | If true (default), validates without deleting. Set to false to actually delete. |
| knowledgeStoreId | string | yes | The knowledge store ID containing the connector |
No output schema declared.
No examples provided.
delete_knowledge_source ~101
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.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without deleting. Set to false to actually delete. |
| knowledgeStoreId | string | yes | The knowledge store ID containing the source |
| sourceId | string | yes | The knowledge source ID to delete |
No output schema declared.
No examples provided.
delete_knowledge_store ~92
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.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without deleting. Set to false to actually delete. |
| knowledgeStoreId | string | yes | The knowledge store ID to delete |
No output schema declared.
No examples provided.
delete_llm ~80
Deletes a Cognigy.AI large language model configuration. WARNING: Features using this LLM will stop working. MUTATING: Set dryRun=false to delete.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without deleting. Set to false to actually delete. |
| largeLanguageModelId | string | yes | The LLM ID to delete |
No output schema declared.
No examples provided.
delete_nlu_connector ~83
Deletes a Cognigy.AI NLU connector. WARNING: Endpoints using this connector will lose NLU functionality. MUTATING: Set dryRun=false to delete.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without deleting. Set to false to actually delete. |
| nluConnectorId | string | yes | The NLU connector ID to delete |
No output schema declared.
No examples provided.
delete_node ~116
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.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates the operation without deleting. Set to false to actually delete. WARNING: Deletion cannot be undone via API. |
| flowId | string | yes | The flow ID containing the node to delete |
| nodeId | string | yes | The ID of the node to delete |
No output schema declared.
No examples provided.
delete_package ~138
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.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without deleting. Set to false to actually delete. WARNING: This is irreversible! |
| packageId | string | yes | The package ID to delete |
| pollIntervalMs | integer | – | How often to check task status (1-10 seconds, default 2) |
| timeoutMs | integer | – | Maximum time to wait for deletion (5-300 seconds, default 60) |
No output schema declared.
No examples provided.
delete_snapshot ~142
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.
| Name | Type | Req | Description |
|---|---|---|---|
| dryRun | boolean | – | If true (default), validates without deleting. Set to false to actually delete. WARNING: This is irreversible! |
| pollIntervalMs | integer | – | How often to check task status (1-10 seconds, default 2) |
| snapshotId | string | yes | The snapshot ID to delete |
| timeoutMs | integer | – | Maximum time to wait for deletion (5-300 seconds, default 60) |
No output schema declared.
No examples provided.
diff_snapshots ~112
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.
| Name | Type | Req | Description |
|---|---|---|---|
| resourceTypes | array | – | Types of resources to compare. Supported: flow, nluconnector, locale, largeLanguageModel (default: all) |
| snapshotIdA | string | yes | The 'before' snapshot ID (base for comparison) |
| snapshotIdB | string | yes | The 'after' snapshot ID (what changed) |
No output schema declared.
No examples provided.
export_contact_profile ~54
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.
| Name | Type | Req | Description |
|---|---|---|---|
| profileId | string | yes | The contact profile ID to export |
No output schema declared.
No examples provided.
generate_nlu_scores ~115
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.
| Name | Type | Req | Description |
|---|---|---|---|
| flowReferenceId | string | yes | The reference ID (UUID) of the flow to score against |
| localeReferenceId | string | yes | The reference ID (UUID) of the locale |
| projectId | string | yes | The project ID containing the flow |
| sentence | string | yes | The test utterance to score against trained intents |
No output schema declared.
No examples provided.
generate_node_output ~194
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.
| Name | Type | Req | Description |
|---|---|---|---|
| flowId | string | yes | The flow ID (used for context, e.g., persona settings) |
| generateContentLimit | integer | – | Maximum number of text variations to generate (for text output type, 1-10) |
| lastOutput | string | – | Previous generation result to refine or continue from |
| localeId | string | yes | The locale ID for language-appropriate generation |
| outputType | string | – | Type of content to generate: 'text' for plain Say messages, 'adaptiveCard' for rich interactive cards |
| prompt | string | yes | Natural language description of what content to generate (e.g., 'greeting message for a banking bot', 'poll for scheduling a meeting') |
No output schema declared.
No examples provided.
generate_sentences ~109
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.
| Name | Type | Req | Description |
|---|---|---|---|
| flowId | string | yes | The flow ID containing the intent |
| intentId | string | yes | The intent ID to generate sentences for |
| limit | integer | – | Number of sentences to generate (5-20, default 5) |
| localeId | string | – | Optional locale ID for locale-specific generation |
No output schema declared.
No examples provided.
get_audit_event ~49
Gets detailed information about a specific Cognigy.AI audit event. Returns the full change details including before/after values.
| Name | Type | Req | Description |
|---|---|---|---|
| auditEventId | string | yes | The audit event ID to retrieve |
No output schema declared.
No examples provided.
get_call_metrics ~116
Gets Cognigy.AI call counter metrics (Voice Gateway). Returns aggregated call counts for a project or entire organization over a time period.
| 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_connection ~61
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.
| Name | Type | Req | Description |
|---|---|---|---|
| connectionId | string | yes | The connection ID to retrieve |
No output schema declared.
No examples provided.
get_contact_profile ~47
Gets detailed information about a specific Cognigy.AI contact profile. Returns stored user data, goals, and profile metadata.
| Name | Type | Req | Description |
|---|---|---|---|
| profileId | string | yes | The contact profile ID to retrieve |
No output schema declared.
No examples provided.
get_contact_profile_schema ~53
Gets the contact profile schema for a Cognigy.AI project. The schema defines what custom fields can be stored in contact profiles.
| Name | Type | Req | Description |
|---|---|---|---|
| projectId | string | yes | The project ID to get the profile schema for |
No output schema declared.
No examples provided.
get_conversation ~74
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.
| Name | Type | Req | Description |
|---|---|---|---|
| projectId | string | – | Optional project ID to scope the query |
| sessionId | string | yes | The session ID to get conversation for |
No output schema declared.
No examples provided.
get_conversation_metrics ~114
Gets Cognigy.AI conversation counter metrics. Returns aggregated conversation counts for a project or entire organization over a time period.
| 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_conversations ~71
Gets conversations for specific contacts in a Cognigy.AI project. Returns conversation history including inputs, outputs, and metadata. Use this to analyze user interactions.
| Name | Type | Req | Description |
|---|---|---|---|
| contactIds | array | yes | Array of contact IDs to get conversations for |
| projectId | string | yes | The project ID to get conversations from |
No output schema declared.
No examples provided.
get_endpoint ~53
Gets detailed configuration of a specific Cognigy.AI endpoint. Returns channel settings, flow/agent binding, and runtime configuration. Use this to inspect endpoint behavior.
| Name | Type | Req | Description |
|---|---|---|---|
| endpointId | string | yes | The endpoint ID to retrieve |
No output schema declared.
No examples provided.
get_extension ~46
Gets detailed information about a specific Cognigy.AI Extension. Returns package info, available nodes, connections schemas, and settings.
| Name | Type | Req | Description |
|---|---|---|---|
| extensionId | string | yes | The extension ID to retrieve |
No output schema declared.
No examples provided.
What is the io.github.TsvetanG2/cognigy-ai-mcp-management-server server?
io.github.TsvetanG2/cognigy-ai-mcp-management-server is listed in the public MCP registry as io.github.TsvetanG2/cognigy-ai-mcp-management-server. MCP server for Cognigy.AI - 132 tools to build, configure & operate conversational AI agents. This page covers its npm package (cognigy-ai-mcp-management-server).
Is the io.github.TsvetanG2/cognigy-ai-mcp-management-server server safe to use?
io.github.TsvetanG2/cognigy-ai-mcp-management-server scores 80 out of 100 on VerifyMCP. We recorded 14 known advisories against it as of 2 October 2026. It declares no install or post-install scripts. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the io.github.TsvetanG2/cognigy-ai-mcp-management-server server expose?
io.github.TsvetanG2/cognigy-ai-mcp-management-server exposes 138 tools: list_projects, list_flows, get_flow, get_flow_settings, get_latest_log_entries, and 133 more. Their descriptions and schemas cost roughly 14,859 tokens of context every time the server is loaded.
Is the io.github.TsvetanG2/cognigy-ai-mcp-management-server server still maintained?
io.github.TsvetanG2/cognigy-ai-mcp-management-server is still listed as active in the MCP registry. We last reached this channel on 2 October 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the io.github.TsvetanG2/cognigy-ai-mcp-management-server server under?
io.github.TsvetanG2/cognigy-ai-mcp-management-server declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.