mirror of
https://github.com/msoedov/agentic_security.git
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chore: delete Agno dead code (Phase 1)
Closes #307 Agno was imported by nothing, had undefined-variable bugs, and was not a declared dependency. Removed: - agentic_security/agents/ (operator_agno.py) - docs/mcp_agno_integration.md - .gitignore reference to operator_agno.py No agno references remain in source code. Pre-existing test failures (missing tabulate module) confirmed unrelated to this change via git stash verification.
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@@ -19,9 +19,11 @@ docx/
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agentic_security.toml
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/venv
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*.csv
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agentic_security/agents/operator_agno.py
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.claude/
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plan.md
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auto_loop.sh
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agentic_security/static/elm-stuff/
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agentic_security/static/node_modules/
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.cache/
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COMMIT_MSG.txt
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@@ -1,156 +0,0 @@
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# MCP + Agno Integration
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This guide shows how to use Agentic Security's MCP server with [Agno](https://docs.agno.com/tools/mcp) agents.
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## Setup
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Install Agentic Security with optional Agno support:
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```bash
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pip install agno
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```
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## Starting the MCP Server
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Start the Agentic Security MCP server:
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```bash
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python -m agentic_security.mcp.main
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```
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For production, use the stdio transport (default with FastMCP):
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```bash
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python agentic_security/mcp/main.py
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```
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## Examples
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### Basic Verification with Agno
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```python
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import asyncio
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from agno.agent import Agent
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from agno.tools.mcp import MCPTools
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from agentic_security.mcp.main import mcp
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async def verify_llm_spec():
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# Connect to Agentic Security's MCP server via stdio
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mcp_tools = MCPTools(
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command="python",
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args=["agentic_security/mcp/main.py"],
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)
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await mcp_tools.connect()
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try:
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agent = Agent(
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tools=[mcp_tools],
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instructions=[
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"You are a security testing assistant.",
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"Use verify_llm to test LLM specifications for vulnerabilities.",
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"Present results clearly with risk levels.",
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],
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markdown=True,
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)
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await agent.aprint_response(
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"Verify this LLM spec: openai/gpt-4",
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stream=True,
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)
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finally:
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await mcp_tools.close()
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asyncio.run(verify_llm_spec())
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```
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### Running a Security Scan
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```python
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import asyncio
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from agno.agent import Agent
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from agno.tools.mcp import MCPTools
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async def run_security_scan():
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mcp_tools = MCPTools(
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command="python",
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args=["agentic_security/mcp/main.py"],
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)
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await mcp_tools.connect()
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try:
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agent = Agent(
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tools=[mcp_tools],
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instructions=[
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"You are an LLM security scanning assistant.",
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"Use start_scan to initiate security scans on LLM endpoints.",
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"Use get_data_config to check available scan configurations.",
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"Report findings with severity levels.",
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],
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markdown=True,
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)
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await agent.aprint_response(
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"Run a security scan on openai/gpt-4 with max budget 100",
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stream=True,
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)
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finally:
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await mcp_tools.close()
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asyncio.run(run_security_scan())
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```
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### Streamable HTTP Transport
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```python
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import asyncio
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from agno.agent import Agent
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from agno.tools.mcp import MCPTools
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async def run_http_transport():
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mcp_tools = MCPTools(
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transport="streamable-http",
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url="http://0.0.0.0:8718/mcp",
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)
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await mcp_tools.connect()
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try:
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agent = Agent(
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tools=[mcp_tools],
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markdown=True,
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)
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await agent.aprint_response(
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"List available security scan templates",
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stream=True,
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)
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finally:
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await mcp_tools.close()
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asyncio.run(run_http_transport())
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```
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## Available Tools
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| Tool | Description |
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|---|---|
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| `verify_llm` | Verify an LLM model specification |
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| `start_scan` | Start an LLM security scan |
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| `stop_scan` | Stop an ongoing scan |
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| `get_data_config` | Retrieve data configuration |
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| `get_spec_templates` | Retrieve LLM specification templates |
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## Notes
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- The stdio transport is recommended for local development
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- For production deployments, use the streamable-http transport
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- Always call `mcp_tools.close()` to clean up connections
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