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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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    1
    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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    Enables MCP clients to interact with A2A agents through four ordinary tools, translating agent discovery, messaging, task reading, and cancellation between the A2A and MCP protocols, with support for the tasks extension.
    31 npm
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    Apache 2.0
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    Enables developers to build and deploy secure, typed Model Context Protocol servers with tools, resources, prompts, bearer-token authentication, per-tool scopes, rate limiting, and health probes over Streamable HTTP.
    MIT
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    A Model Context Protocol server that provides Google Jobs search capabilities through SerpAPI integration, featuring multi-language support, flexible search parameters, and rich job details.
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    MIT
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    A comprehensive Google Ads API integration for AI assistants through the Model Context Protocol. This server enables Claude AI and other MCP-compatible clients to manage Google Ads campaigns, analyze performance, and execute GAQL queries with natural language commands.
    76
    MIT
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    Acts as a bridge between standard REST/OpenAPI web APIs and the Model Context Protocol, dynamically converting REST endpoints into MCP tools for LLM clients like Cursor, Claude Desktop, and n8n.
    32 npm
    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