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Glama
vad-007

MCP + CrewAI Agentic Integration

by vad-007

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
GROQ_API_KEYYesAPI Key for Groq to power the LLM engine (Llama 3.1).
SERPER_API_KEYYesAPI Key for Serper (Google Search API) used for news retrieval.
WEATHER_API_KEYYesAPI Key for WeatherAPI to access real-time meteorology data.
AGENTOPS_API_KEYYesAPI Key for AgentOps for observability, tracing, cost management, and debugging.

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": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
add_noteB

Append a new note to the note file.

Args: message (str): The note content to be added.

Returns: str: Confirmation message indicating the note was saved.

search_newsB

Fetch search results from Google News via Serper

fetch_weatherB

Fetch current weather for a city

read_notesB

Read and return all notes from the note file.

Returns: str: All notes as a single string separated by line breaks. If no notes exist, a default message is returned.

Prompts

Interactive templates invoked by user choice

NameDescription
note_summary_prompt Generate a prompt asking the AI to summarize all current notes. Returns: str: A prompt string that includes all notes and asks for a summary. If no notes exist, a message will be shown indicating that.

Resources

Contextual data attached and managed by the client

NameDescription
get_latest_note Get the most recently added note from the note file. Returns: str: The last note entry. If no notes exist, a default message is returned.

TDQS

B3.3/5.0

Scored across 4 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: add_note and read_notes handle note management, fetch_weather retrieves weather data, and search_news fetches news results. There is no overlap in functionality, making tool selection straightforward for an agent.

Naming Consistency4/5

The tool names follow a consistent verb_noun pattern (add_note, fetch_weather, read_notes, search_news), which is predictable and readable. The minor deviation is that 'fetch_weather' and 'search_news' use different verbs ('fetch' vs. 'search'), but the overall pattern remains clear.

Tool Count3/5

With only 4 tools, the set feels thin for a server named 'MCP + CrewAI Agentic Integration', which suggests broader agentic capabilities. While the tools cover basic utilities (notes, weather, news), the scope seems limited compared to the implied integration purpose, bordering on under-scoped.

Completeness2/5

Inferring the domain as agentic integration utilities, there are significant gaps: no tools for agent coordination, task management, or data processing beyond simple fetches. The note tools lack update/delete operations, and overall coverage is incomplete for enabling complex agent workflows.

Maintenance

ActivityInactive
ResponsivenessNo issues