docs: fix Claude Desktop MCP setup, CrewAI guide, and missing contributor docs (#6945)

This commit is contained in:
Kartik
2026-08-20 15:24:05 +05:30
committed by GitHub
parent 001c235229
commit 52b02c7cc1
4 changed files with 90 additions and 42 deletions
+38 -23
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@@ -39,6 +39,10 @@ os.environ["SERPER_API_KEY"] = "your-serper-api-key"
client = MemoryClient()
```
<Note>
Newer versions of CrewAI removed the `memory_config={"provider": "mem0"}` shortcut on `Crew(...)` that older guides referenced. CrewAI still offers a native Mem0 path through its `ExternalMemory` API, so that option remains open; check [CrewAI's memory documentation](https://docs.crewai.com/en/concepts/memory) for the shape your version expects. This guide wires Mem0 in explicitly through `MemoryClient` instead, which keeps retrieval under your control and stays valid as CrewAI's memory API changes.
</Note>
## Store User Preferences
Set up initial conversation and preferences storage:
@@ -69,9 +73,21 @@ messages = [
store_user_preferences("crew_user_1", messages)
```
## Retrieve Relevant Memories
Look up what Mem0 already knows about the user before planning a trip, so the crew's output reflects their actual preferences:
```python
def get_user_context(user_id: str, query: str) -> str:
"""Fetch relevant memories and format them for a task description"""
relevant_memories = client.search(query, filters={"user_id": user_id})
memories = [m["memory"] for m in relevant_memories.get("results", [])]
return "\n".join(f"- {memory}" for memory in memories)
```
## Create CrewAI Agent
Define an agent with memory capabilities:
Define an agent with search capabilities:
```python
def create_travel_agent():
@@ -83,61 +99,60 @@ def create_travel_agent():
goal="Plan personalized travel itineraries",
backstory="""You are a seasoned travel planner, known for your meticulous attention to detail.""",
allow_delegation=False,
memory=True,
tools=[search_tool],
)
```
## Define Tasks
Create tasks for your agent:
Create a task that folds the retrieved memories into its description, so the agent plans around the user's known preferences:
```python
def create_planning_task(agent, destination: str):
"""Create a travel planning task"""
def create_planning_task(agent, destination: str, user_context: str):
"""Create a travel planning task personalized with the user's stored preferences"""
return Task(
description=f"""Find places to live, eat, and visit in {destination}.""",
expected_output=f"A detailed list of places to live, eat, and visit in {destination}.",
description=f"""Find places to live, eat, and visit in {destination}.
Known preferences for this user:
{user_context or "No stored preferences yet."}
""",
expected_output=f"A detailed list of places to live, eat, and visit in {destination}, tailored to the user's preferences.",
agent=agent,
)
```
## Set Up Crew
Configure the crew with memory integration:
Configure the crew. Mem0 handles persistence outside of CrewAI, so the crew itself does not need `memory=True` or a `memory_config`:
```python
def setup_crew(agents: list, tasks: list):
"""Set up a crew with Mem0 memory integration"""
"""Set up a crew; memory is managed through Mem0, not CrewAI's memory_config"""
return Crew(
agents=agents,
tasks=tasks,
process=Process.sequential,
memory=True,
memory_config={
"provider": "mem0",
"config": {"user_id": "crew_user_1"},
}
)
```
## Main Execution Function
Implement the main function to run the travel planning system:
Implement the main function to run the travel planning system: retrieve context from Mem0, run the crew, then store the new conversation back:
```python
def plan_trip(destination: str, user_id: str):
# Create agent
travel_agent = create_travel_agent()
# Create task
planning_task = create_planning_task(travel_agent, destination)
# Setup crew
user_context = get_user_context(user_id, f"travel preferences for {destination}")
planning_task = create_planning_task(travel_agent, destination, user_context)
crew = setup_crew([travel_agent], [planning_task])
result = crew.kickoff()
# Execute and return results
return crew.kickoff()
client.add(
[{"role": "user", "content": f"Planned a trip to {destination}."}],
user_id=user_id,
)
return result
# Example usage
if __name__ == "__main__":