aparajithn/agent-utils-mcp

Overview

A Python package that provides utility functions for AI agents using the Model Context Protocol (MCP). It is listed in the awesome-mcp-servers collection and is intended to simplify agent tool integration and context management.

Best for

Best for
Builders exploring MCP-based agent architectures who need a simple starting point

Use cases

• Building MCP-based agent workflows with minimal boilerplate
• Integrating custom tools into agent context
• Testing and prototyping MCP agent interactions

How to use

Tools exposed

• tool_json_validate
• tool_json_format
• tool_base64_encode
• tool_base64_decode
• tool_hash_generate
• tool_uuid_generate
• tool_url_parse
• tool_regex_test
• tool_markdown_to_html
• tool_html_to_markdown
• tool_text_stats
• tool_slug_generate
• tool_datetime_convert
• tool_cron_parse
• tool_diff_text
• tool_csv_to_json
• tool_json_to_csv
• tool_jwt_decode

Tested with

Claude Desktop, Cursor, Windsurf

Example client config

{\n  "mcpServers": {\n    "agent-utils": {\n      "url": "https://agent-utils-mcp.onrender.com/mcp"\n    }\n  }\n}

Notes

A Python package that provides utility functions for AI agents using the Model Context Protocol (MCP). It is listed in the awesome-mcp-servers collection and is intended to simplify agent tool integration and context management.

4 stars on GitHub. Last updated 2026-03-07.

Use cases

• Building MCP-based agent workflows with minimal boilerplate
• Integrating custom tools into agent context
• Testing and prototyping MCP agent interactions

Pros

• Lightweight and Python-native
• Focused on MCP standard for agent interoperability
• Useful as a foundation for custom agent utilities

Cons

• Very low community adoption (4 stars) and sparse documentation
• May lack maturity and feature coverage for production use
• Limited visibility beyond the awesome-mcp-servers listing

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.