Use Artifacta with CrewAI

pip install artifacta-mcp 'crewai-tools[mcp]' crewai
export ARTIFACTA_API_KEY=ak_live_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

from crewai_tools import MCPServerAdapter
from mcp import StdioServerParameters
from artifacta_mcp import build_stdio_params

# allow_path: let store_artifact read local files from this dir.
# allow_destructive: expose create_download_link / delete_artifact / seal_session.
server_params = StdioServerParameters(
    **build_stdio_params(allow_path="/abs/path/to/work", allow_destructive=False)
)

with MCPServerAdapter(server_params) as artifacta_tools:
    print("Artifacta tools:", [t.name for t in artifacta_tools])
    # ... build agents with tools=artifacta_tools (see below) ...

import os
from crewai import Agent, Task, Crew, Process
from crewai_tools import MCPServerAdapter
from mcp import StdioServerParameters
from artifacta_mcp import build_stdio_params

server_params = StdioServerParameters(**build_stdio_params())
SESSION_ID = "crewai_handoff_demo"

with MCPServerAdapter(server_params) as artifacta_tools:
    researcher = Agent(
        role="Researcher",
        goal="Write a short brief and store it in Artifacta for the editor.",
        backstory="You produce first drafts and persist them as artifacts.",
        tools=artifacta_tools,
        verbose=True,
    )
    editor = Agent(
        role="Editor",
        goal="Retrieve the researcher's stored artifact and improve it.",
        backstory="You fetch artifacts by id and refine their content.",
        tools=artifacta_tools,
        verbose=True,
    )

    write_task = Task(
        description=(
            "Write a 5-bullet brief on why agents need an artifact store. "
            f"Store it in Artifacta with store_artifact under session_id='{SESSION_ID}' "
            "and metadata kind=brief. Report the resulting artifact id."
        ),
        expected_output="The art_… id of the stored brief.",
        agent=researcher,
    )
    edit_task = Task(
        description=(
            "Using the artifact id from the researcher, call get_artifact (and "
            "get_artifact_download_url if you need the bytes) to retrieve the brief, "
            "then produce an improved version."
        ),
        expected_output="The improved brief.",
        agent=editor,
        context=[write_task],  # the researcher's output (the artifact id) feeds the editor
    )

    crew = Crew(
        agents=[researcher, editor],
        tasks=[write_task, edit_task],
        process=Process.sequential,
        verbose=True,
    )
    result = crew.kickoff()
    print(result)