diff --git a/docs/deploy/mcp-server-deploy.mdx b/docs/deploy/mcp-server-deploy.mdx
index c538606c9..ee0111d39 100644
--- a/docs/deploy/mcp-server-deploy.mdx
+++ b/docs/deploy/mcp-server-deploy.mdx
@@ -15,12 +15,12 @@ This guide focuses on deploying Model Context Protocol (MCP) servers for product
Make sure you have the required packages installed:
```bash
- pip install "praisonaiagents[mcp]>=0.0.81"
+ pip install "praisonaiagents[mcp]"
```
For the multi-agent example with search capabilities:
```bash
- pip install "praisonaiagents[mcp]>=0.0.81" duckduckgo-search
+ pip install "praisonaiagents[mcp]" duckduckgo-search
```
@@ -30,12 +30,12 @@ This guide focuses on deploying Model Context Protocol (MCP) servers for product
```python
from praisonaiagents import Agent
- agent = Agent(name="TweetAgent", instructions="Create a Tweet based on the topic provided")
+ agent = Agent(instructions="Create a Tweet based on the topic provided")
agent.launch(port=8080, host="0.0.0.0", protocol="mcp")
```
**Multi-Agent MCP Server with Custom Tools**
-
+
Create a file named `simple-mcp-multi-agents-server.py`:
```python
from praisonaiagents import Agent, Agents
@@ -52,10 +52,44 @@ This guide focuses on deploying Model Context Protocol (MCP) servers for product
})
return results
- agent = Agent(name="SearchAgent", instructions="You Search the internet for information", tools=[internet_search_tool])
- agent2 = Agent(name="SummariseAgent", instructions="You Summarise the information")
+ agent = Agent(instructions="You Search the internet for information", tools=[internet_search_tool])
+ agent2 = Agent(instructions="You Summarise the information")
+
+ agents = Agents(agents=[agent, agent2])
+ agents.launch(port=8080, host="0.0.0.0", protocol="mcp")
+ ```
+
+ **Simple Multi-Agent MCP Server**
+
+ Create a file named `simple-multi-agents-server.py`:
+ ```python
+ from praisonaiagents import Agent, Agents
+
+ agent = Agent(instructions="You Search the internet for information")
+ agent2 = Agent(instructions="You Summarise the information")
+
+ agents = Agents(agents=[agent, agent2])
+ agents.launch(port=8080, host="0.0.0.0", protocol="mcp")
+ ```
+ ```python
+ from praisonaiagents import Agent, Agents
+ from duckduckgo_search import DDGS
+
+ def internet_search_tool(query: str):
+ results = []
+ ddgs = DDGS()
+ for result in ddgs.text(keywords=query, max_results=5):
+ results.append({
+ "title": result.get("title", ""),
+ "url": result.get("href", ""),
+ "snippet": result.get("body", "")
+ })
+ return results
+
+ agent = Agent(instructions="You Search the internet for information", tools=[internet_search_tool])
+ agent2 = Agent(instructions="You Summarise the information")
- agents = Agents(name="MultiAgents", agents=[agent, agent2])
+ agents = Agents(agents=[agent, agent2])
agents.launch(port=8080, host="0.0.0.0", protocol="mcp")
```
@@ -86,7 +120,7 @@ This guide focuses on deploying Model Context Protocol (MCP) servers for product
Create a `requirements.txt` file:
```
- praisonaiagents[mcp]>=0.0.81
+ praisonaiagents[mcp]
duckduckgo-search # Only needed for the multi-agent example
```
diff --git a/docs/mcp/mcp-server.mdx b/docs/mcp/mcp-server.mdx
index ca3e9d70d..66d67a1f7 100644
--- a/docs/mcp/mcp-server.mdx
+++ b/docs/mcp/mcp-server.mdx
@@ -1,5 +1,5 @@
---
-title: "Creating MCP Servers"
+title: "MCP Servers"
sidebarTitle: "MCP Servers"
description: "Learn how to create Model Context Protocol (MCP) servers with PraisonAI agents"
icon: "server"
@@ -25,7 +25,7 @@ The simplest way to create an MCP server is with a single agent. This approach i
```python
from praisonaiagents import Agent
- agent = Agent(name="TweetAgent", instructions="Create a Tweet based on the topic provided")
+ agent = Agent(instructions="Create a Tweet based on the topic provided")
agent.launch(port=8080, protocol="mcp")
```
@@ -45,7 +45,7 @@ For more complex scenarios, you can create an MCP server with multiple agents an
```bash
- pip install "praisonaiagents[mcp]>=0.0.81" duckduckgo-search
+ pip install "praisonaiagents[mcp]" duckduckgo-search
```
@@ -65,10 +65,10 @@ For more complex scenarios, you can create an MCP server with multiple agents an
})
return results
- agent = Agent(name="SearchAgent", instructions="You Search the internet for information", tools=[internet_search_tool])
- agent2 = Agent(name="SummariseAgent", instructions="You Summarise the information")
+ agent = Agent(instructions="You Search the internet for information", tools=[internet_search_tool])
+ agent2 = Agent(instructions="You Summarise the information")
- agents = Agents(name="MultiAgents", agents=[agent, agent2])
+ agents = Agents(agents=[agent, agent2])
agents.launch(port=8080, protocol="mcp")
```
@@ -81,6 +81,22 @@ For more complex scenarios, you can create an MCP server with multiple agents an
+## Multi-Agent MCP Server (Simple)
+
+For scenarios where you need multiple agents to collaborate without custom tools, you can create a simpler multi-agent MCP server:
+
+```python
+from praisonaiagents import Agent, Agents
+
+agent = Agent(instructions="You Search the internet for information")
+agent2 = Agent(instructions="You Summarise the information")
+
+agents = Agents(agents=[agent, agent2])
+agents.launch(port=8080, protocol="mcp")
+```
+
+This approach is ideal for cases where you want agents with different specializations to work together using their built-in capabilities.
+
## Connecting to MCP Servers
You can connect to MCP servers using various clients: