nestjs-langgraph-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OLLAMA_MODEL | No | Ollama model name (default: 'qwen2.5:1.5b') | |
| OPENAI_MODEL | No | OpenAI model name (default: 'gpt-4o-mini') | |
| MODEL_PROVIDER | No | Model provider: 'openai' or 'ollama'. Default is 'ollama'. | ollama |
| OPENAI_API_KEY | No | OpenAI API key (required if using OpenAI provider) | |
| OLLAMA_BASE_URL | No | Ollama base URL (default: 'http://localhost:11434') |
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
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| main_agentA | The main orchestration agent that can handle any request by leveraging all available tools. Capabilities:
Use this as the primary interface for all requests. |
| list_agentsA | Returns information about all available agents and their tools. |
| run_agentC | Runs a LangGraph-orchestrated NestJS agent with optional provider/model selection. |
| healthA | Returns basic server status and default model configuration. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Health and list_agents are clear, but main_agent and run_agent overlap: both execute agents, with main_agent claiming to handle any request and run_agent offering provider/model selection. This could cause confusion about which to use.
Tool names mix conventions: 'health' is a noun, 'list_agents' and 'run_agent' are verb_noun, 'main_agent' is adjective_noun. Verbs are not consistently used, leading to an incoherent pattern.
With only 4 tools, the server feels thin for the advertised capabilities (employee data, analytics, reporting, approval). The count is borderline but not extremely low for an agent-centric design.
The server lists numerous capabilities (e.g., list employees, engagement scores) but lacks dedicated tools for them—all are funneled through main_agent. This creates a gap where agents cannot directly perform specific operations.