Built for AI Agents

from crewai_tools import BaseTool
from pydantic import BaseModel, Field
import requests, os

SLOPSHOP_KEY = os.environ["SLOPSHOP_KEY"]

class SlopshopInput(BaseModel):
    tool: str = Field(description="Slopshop tool slug e.g. crypto-hash-sha256")
    payload: dict = Field(description="JSON payload for the tool")

class SlopshopTool(BaseTool):
    name: str = "slopshop"
    description: str = ("Call any of the Slopshop utility APIs. Use the semantic resolver "
                        "to find the right tool: POST /v1/resolve {\"query\": \"what you need\"}")
    args_schema = SlopshopInput

    def _run(self, tool: str, payload: dict) -> dict:
        r = requests.post(
            f"https://slopshop.gg/v1/{tool}",
            headers={"Authorization": f"Bearer {SLOPSHOP_KEY}"},
            json=payload
        )
        return r.json()["data"]

from crewai import Agent, Task, Crew

analyst = Agent(
    role="Data Analyst",
    goal="Process and analyze data using real computation tools",
    tools=[SlopshopTool()],
    verbose=True
)
task = Task(
    description="Hash the user passwords in this list with SHA-256 and return the hashes",
    agent=analyst
)
crew = Crew(agents=[analyst], tasks=[task])
crew.kickoff()

# Install the Slopshop MCP server
npm install -g @slopshop/mcp

# Add to Claude Code (single command)
claude mcp add slopshop -- slopshop-mcp --key $SLOPSHOP_KEY

# Or manually in .claude/settings.json:
{
  "mcpServers": {
    "slopshop": {
      "command": "slopshop-mcp",
      "args": ["--key", "sk-slop-your-key-here"],
      "env": {}
    }
  }
}

# Claude will now auto-discover the full catalog of tools via:
# GET /v1/tools?format=mcp
# And call them natively during any conversation.

import anthropic, requests, json, os

slopshop_key = os.environ["SLOPSHOP_KEY"]
client = anthropic.Anthropic()

# Fetch tools in Anthropic format
tools = requests.get(
    "https://slopshop.gg/v1/tools?format=anthropic&limit=50",
    headers={"Authorization": f"Bearer {slopshop_key}"}
).json()["tools"]

def call_tool(name: str, inputs: dict) -> str:
    r = requests.post(
        f"https://slopshop.gg/v1/{name}",
        headers={"Authorization": f"Bearer {slopshop_key}"},
        json=inputs
    )
    return json.dumps(r.json()["data"])

# Agentic loop
messages = [{"role": "user", "content": "Hash 'hello world' with SHA-256"}]
while True:
    resp = client.messages.create(model="claude-opus-4-6", max_tokens=1024, tools=tools, messages=messages)
    if resp.stop_reason == "end_turn": break
    tool_use = [b for b in resp.content if b.type == "tool_use"]
    if not tool_use: break
    messages.append({"role": "assistant", "content": resp.content})
    results = [{"type": "tool_result", "tool_use_id": t.id, "content": call_tool(t.name, t.input)} for t in tool_use]
    messages.append({"role": "user", "content": results})