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    Paybond Kit for Python is the PyPI package for tenant-bound Paybond integrations and delegated agent spend controls. It opens hosted Gateway sessions, verifies capability tokens, authorizes tool-call spend, signs intent and evidence payloads, uses Stripe Connect, Stripe ACH Direct Debit, or x402 / USDC-on-Base settlement rails, reads tenant-scoped Signal, fraud, ledger, protocol, and A2A data, and
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    Apache 2.0
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    A Python implementation of the Model Context Protocol that allows applications to provide standardized context for LLMs, enabling creation of servers that expose data and functionality to LLM applications through resources, tools, and prompts.
    MIT
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    A Machine Comprehension Protocol server that enables AI assistants to interact with Kestra workflows through natural language, supporting operations like flow management, executions, backfills, and other Kestra features.
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    Apache 2.0
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    A Python package that implements a Model Context Protocol server for integrating with Flowise API, allowing users to list chatflows, create predictions, and dynamically register tools for Flowise chatflows or assistants.
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    MIT
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    A Python-based MCP server that allows Claude and other LLMs to execute arbitrary Python code directly through your desktop Claude app, enabling data scientists to connect LLMs to APIs and executable code.
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    MIT
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    A declarative framework that manages LLM resources, prompts, and tools through YAML configuration files. It enables LLMs to interact with external data, CLI commands, and Python functions using the Model Context Protocol.
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    MIT
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    A public chat platform for AI agents with MCP and A2A support, enabling agent-to-agent communication across channels via a single-file Python server.
    MIT
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    A lightweight server for Samsung SmartThings, offering tools to manage devices and rooms. Features include room mapping, device listing, status checks, and command execution. #IoT, #Python, #HomeAutomation #Smartthings
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    MIT
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    Bridges Llama models with Claude Desktop through Ollama, enabling privacy-first local AI operations with 10+ built-in tools for file operations, web search, calculations, and custom model deployment. Features streaming support, hybrid intelligence workflows, and extensive Python ecosystem integration for research, development, and enterprise applications.
    MIT
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    Enables interaction with a TrueRAG system through a GraphQL API using the Model Context Protocol (MCP), facilitating access to policies with a Python SDK and GQL library integration.
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