ChipsAI MCP Server vs Plugin Engine
A side-by-side look at the ChipsAI MCP Server and Plugin Engine MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose ChipsAI MCP Server for conversational ai work as a local process; choose Plugin Engine for conversational ai as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose ChipsAI MCP Server when
- You need dedicated capabilities in the Conversational AI domain.
- You prefer a local stdio subprocess transport.
- You have the keys it needs:
CHIPSAI_API_KEY, CHIPSAI_API_URL, CHIPSAI_USERNAME, CHIPSAI_PASSWORD. - You want tools like
list_chatbots, get_chatbot, create_chatbot.
Choose Plugin Engine when
- You need dedicated capabilities in the Conversational AI domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
COGNIGY_API_BASE_URL, COGNIGY_API_KEY. - You want tools like
create_ai_agent, update_ai_agent, setup_llm.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Conversational AI | Conversational AI |
| Quality signal | 47/100 · Fair | 61/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | API key required |
| Pricing | Not declared | BYOK (pay the provider) |
| Required env vars | CHIPSAI_API_KEYCHIPSAI_API_URLCHIPSAI_USERNAMECHIPSAI_PASSWORD | COGNIGY_API_BASE_URLCOGNIGY_API_KEY |
| Verified owner | Community listing | Community listing |
| GitHub stars | 0 | 18 |
| Directory activity | 0 views 0 installs 0 upvotes | 0 views 0 installs 0 upvotes |
| Tools | 25 | 18 |
| Full listing | View ChipsAI MCP Server | View Plugin Engine |
Tools & capabilities
ChipsAI MCP Server tools 25
list_chatbotsList all chatbots for the authenticated userget_chatbotGet full chatbot details (prompt, model, colors, etc.)create_chatbotCreate a new chatbot (returns embed script tag)update_chatbotUpdate chatbot fields (name, prompt, model, theme, colors, etc.)delete_chatbotSoft-delete (deactivate) a chatbotget_chatbot_configGet public widget configurationget_chatbot_analyticsGet analytics: messages, sessions, daily stats, devices, countriesupload_documentUpload PDF/DOC/DOCX to a chatbot's knowledge base (LlamaParse)list_conversationsList conversations, optionally filtered by chatbotcreate_conversationCreate a new conversationget_conversationGet conversation detailsupdate_conversationUpdate conversation title- +13 more on the listing page
Plugin Engine tools 18
create_ai_agentCreate a complete AI Agent with auto-provisioned flow, job node, and REST endpointupdate_ai_agentUpdate persona, guardrails, job config (role, procedures, LLM, temperature)setup_llmCreate an LLM resource (GPT-4, Claude, Mistral, etc.) with automatic connection validationtalk_to_agentSend a message to an AI Agent and get its response (uses Endpoint Test Mode, so it is not counted as billable)list_resourcesList projects, agents, flows, endpoints, LLMs, knowledge stores, and moreget_resourceGet detailed information about a single resourcedelete_resourcePermanently delete a resourcemanage_knowledgeCreate knowledge stores, add sources (URL, text, file), list chunks for RAGcreate_toolAdd a tool (HTTP, knowledge, email, MCP, A2A) to an agent's job nodeupdate_toolUpdate an existing tool node's configurationmanage_webchatCreate or configure a Webchat v3 endpoint for website deploymentmanage_flow_nodesCreate, update, delete, or list flow nodes for conversation logic- +6 more on the listing page
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
ChipsAI MCP Server
{
"mcpServers": {
"chipsai-mcp-server": {
"command": "uvx",
"args": [
"chipsai-mcp"
],
"env": {
"CHIPSAI_API_KEY": "YOUR_CHIPSAI_API_KEY_HERE",
"CHIPSAI_API_URL": "YOUR_CHIPSAI_API_URL_HERE",
"CHIPSAI_USERNAME": "YOUR_CHIPSAI_USERNAME_HERE",
"CHIPSAI_PASSWORD": "YOUR_CHIPSAI_PASSWORD_HERE"
}
}
}
}
Plugin Engine
{
"mcpServers": {
"cognigy-plugin-engine": {
"command": "npx",
"args": [
"-y",
"-p",
"@cognigy/plugin-engine@latest",
"cognigy-setup"
],
"env": {
"COGNIGY_API_BASE_URL": "YOUR_COGNIGY_API_BASE_URL_HERE",
"COGNIGY_API_KEY": "YOUR_COGNIGY_API_KEY_HERE"
}
}
}
}
Frequently asked questions
ChipsAI MCP Server is categorized under Conversational AI and uses a local stdio subprocess. Plugin Engine belongs to Conversational AI and uses a local stdio subprocess. Pick ChipsAI MCP Server for conversational ai work and Plugin Engine for conversational ai.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
ChipsAI MCP Server has no declared pricing — check the project's own site. Plugin Engine is bring-your-own-key: usage is billed by the API provider you supply a key for. Auth: api key required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add chipsai-mcp-server and cognigy-plugin-engine as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, ChipsAI MCP Server has a quality signal of 47/100 (Fair) with 0 views, 0 installs and 0 GitHub stars. Plugin Engine has 61/100 (Good) with 0 views, 0 installs and 18 GitHub stars.