### Why you’re seeing **`name 'batch_mcp_flow' is not defined`**

1. In **`swarms/structs/agent.py`** the method `mcp_execution_flow()` (or the block that calls MCP) still tries to invoke `batch_mcp_flow`.
2. At the very top of the file the import that *defines* that symbol was commented out when you switched to fast‑MCP:

```python
# from swarms.tools.mcp_integration import (
#     MCPServerSseParams,
#     batch_mcp_flow,          #  ← you lost this
#     mcp_flow_get_tool_schema,
# )
```

3. When Python hits `batch_mcp_flow(…)` it isn’t in the module’s namespace, so the call blows up and your agent prints the MCP‑error.

---

## Two‑step fix

> Below assumes your `swarms/tools/mcp_integration.py` already contains a working (sync) wrapper named `batch_mcp_flow` that *returns a string*, **not** a coroutine object.  
> If you kept it **async**, see the “If your wrapper is still async” note at the end.

---

### 1  · Restore the import in **`agent.py`**

Un‑comment (or add) the line:

```python
from swarms.tools.mcp_integration import batch_mcp_flow
```

Keep the `MCPServerSseParams` import too if you reference it elsewhere.

---

### 2  · Make sure `batch_mcp_flow()` is **synchronous**

Inside **`swarms/tools/mcp_integration.py`** do something like:

```python
# ── swarms/tools/mcp_integration.py ─────────────────────
import asyncio
# … other imports …

async def _batch_mcp_flow_async(
    params: list[MCPServerSseParams],
    function_call: dict[str, Any],
) -> str:
    # your existing async logic that talks to MCP
    # and returns a JSON‑serialisable string/str
    ...

def batch_mcp_flow(
    params: list[MCPServerSseParams],
    function_call: dict[str, Any],
) -> str:
    """Blocking wrapper so callers don't have to await."""
    return asyncio.run(
        _batch_mcp_flow_async(params, function_call)
    )
```

Now `agent.py` can call `batch_mcp_flow(...)` directly and
get **the tool’s real answer**, not a coroutine object.

---

### Quick checklist

- [ ] Re‑import `batch_mcp_flow` in `swarms/structs/agent.py`.
- [ ] Ensure `batch_mcp_flow()` (the public one) **returns a value**, not a coroutine.
- [ ] Remove or comment out the temporary warning prints you added earlier.

---

### If your wrapper is still async

You can alternatively **await** it inside `mcp_execution_flow`:

```python
import asyncio

def mcp_execution_flow(self, response: str) -> str:
    try:
        resp_dict = json.loads(response)
        return asyncio.run(
            batch_mcp_flow(self.mcp_servers, resp_dict)
        )
    except Exception as e:
        logger.error(f"MCP flow failed: {e}")
        return f"[MCP-error] {e}"
```

Either approach works; the key is that the call you make inside the agent must not leave a bare coroutine object floating around.

Once those two lines are fixed, run the client again:

```bash
python examples/mcp_example/mcp_client.py
```

You should now see a clean answer:

```
Enter your query (or 'exit' to quit): add 3 and 33
Math Agent Response: 36
```

Happy calculating!