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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 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 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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    An MCP server that allows Claude Desktop to access and manage Raindrop.io bookmarks through natural language commands, supporting operations for collections, raindrops, and tags.
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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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    A local-first MCP server that snapshots project working state into a structured context object, enabling agents to share and resume sessions seamlessly without leaving your machine.
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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 server that implements the Model Completion Protocol (MCP) to allow LLMs to interact with Databricks resources including clusters, jobs, notebooks, and SQL execution through natural language.
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    MIT
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    A ready-to-use starter implementation of the Model Context Protocol (MCP) server that enables applications to provide standardized context for LLMs with sample resources, tools, and prompts.
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    Agent-native headless browser for AI agents. Converts web pages to a Semantic Object Model (SOM) instead of raw HTML — 17x average token reduction across real-world sites (up to 117x on complex pages). Native MCP server with fetch_page, extract_text, extract_links, and full browser automation. No API key required.
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    Apache 2.0
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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