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1000 results for “infoq”

  1. #Cloudflare announced the closed beta of Flagship - a feature flag service built directly into its global edge platform.

    Teams can control feature rollouts and experiment without redeploying code, while evaluating flags locally in Cloudflare Workers instead of calling external flag services.

    Learn more ⇨ bit.ly/4wdUHQL

    #InfoQ #DevOps #ContinuousDelivery #LowLatency #EdgeComputing

  2. #Cloudflare announced the closed beta of Flagship - a feature flag service built directly into its global edge platform.

    Teams can control feature rollouts and experiment without redeploying code, while evaluating flags locally in Cloudflare Workers instead of calling external flag services.

    Learn more ⇨ bit.ly/4wdUHQL

    #InfoQ #DevOps #ContinuousDelivery #LowLatency #EdgeComputing

  3. #Cloudflare announced the closed beta of Flagship - a feature flag service built directly into its global edge platform.

    Teams can control feature rollouts and experiment without redeploying code, while evaluating flags locally in Cloudflare Workers instead of calling external flag services.

    Learn more ⇨ bit.ly/4wdUHQL

    #InfoQ #DevOps #ContinuousDelivery #LowLatency #EdgeComputing

  4. #Cloudflare announced the closed beta of Flagship - a feature flag service built directly into its global edge platform.

    Teams can control feature rollouts and experiment without redeploying code, while evaluating flags locally in Cloudflare Workers instead of calling external flag services.

    Learn more ⇨ bit.ly/4wdUHQL

    #InfoQ #DevOps #ContinuousDelivery #LowLatency #EdgeComputing

  5. announced the closed beta of Flagship - a feature flag service built directly into its global edge platform.

    Teams can control feature rollouts and experiment without redeploying code, while evaluating flags locally in Cloudflare Workers instead of calling external flag services.

    Learn more ⇨ bit.ly/4wdUHQL

  6. #JobRunr just launched ClawRunr — an #opensource Java AI agent for scheduled, recurring, and one-off background tasks.

    Runs on users' hardware and combines:
    • Conversational interaction with persistent task execution
    • MCP tools
    • Browser automation
    • Web, Telegram & Discord channels

    More details ⇨ bit.ly/4tdBCvz

    #Java #InfoQ

  7. CodeGuardian is an MCP server that extends AI coding assistants with comprehensive code quality and security analysis.

    Developers can access enterprise-grade analysis directly in their AI assistant - reducing context switching and making secure coding easier to adopt.

    🔗 Read now: bit.ly/4u0VNhz

    #InfoQ #AI #ModelContextProtocol #AIagents #AIAssistedCoding

  8. CodeGuardian is an MCP server that extends AI coding assistants with comprehensive code quality and security analysis.

    Developers can access enterprise-grade analysis directly in their AI assistant - reducing context switching and making secure coding easier to adopt.

    🔗 Read now: bit.ly/4u0VNhz

    #InfoQ #AI #ModelContextProtocol #AIagents #AIAssistedCoding

  9. CodeGuardian is an MCP server that extends AI coding assistants with comprehensive code quality and security analysis.

    Developers can access enterprise-grade analysis directly in their AI assistant - reducing context switching and making secure coding easier to adopt.

    🔗 Read now: bit.ly/4u0VNhz

    #InfoQ #AI #ModelContextProtocol #AIagents #AIAssistedCoding

  10. CodeGuardian is an MCP server that extends AI coding assistants with comprehensive code quality and security analysis.

    Developers can access enterprise-grade analysis directly in their AI assistant - reducing context switching and making secure coding easier to adopt.

    🔗 Read now: bit.ly/4u0VNhz

    #InfoQ #AI #ModelContextProtocol #AIagents #AIAssistedCoding

  11. CodeGuardian is an MCP server that extends AI coding assistants with comprehensive code quality and security analysis.

    Developers can access enterprise-grade analysis directly in their AI assistant - reducing context switching and making secure coding easier to adopt.

    🔗 Read now: bit.ly/4u0VNhz

  12. Cloudflare’s new #ModelContextProtocol (MCP) server powered by Code Mode enables #AIagents to interact with large APIs with minimal token usage.

    The server reduces context footprint across 2,500+ endpoints, improves multi-API orchestration, and provides a secure, code-centric execution environment for LLM agents.

    Deep dive on #InfoQbit.ly/4dTJgqQ

    #SoftwareArchitecture #LLMs #API

  13. Cloudflare’s new #ModelContextProtocol (MCP) server powered by Code Mode enables #AIagents to interact with large APIs with minimal token usage.

    The server reduces context footprint across 2,500+ endpoints, improves multi-API orchestration, and provides a secure, code-centric execution environment for LLM agents.

    Deep dive on #InfoQbit.ly/4dTJgqQ

    #SoftwareArchitecture #LLMs #API

  14. Cloudflare’s new #ModelContextProtocol (MCP) server powered by Code Mode enables #AIagents to interact with large APIs with minimal token usage.

    The server reduces context footprint across 2,500+ endpoints, improves multi-API orchestration, and provides a secure, code-centric execution environment for LLM agents.

    Deep dive on #InfoQbit.ly/4dTJgqQ

    #SoftwareArchitecture #LLMs #API

  15. Cloudflare’s new #ModelContextProtocol (MCP) server powered by Code Mode enables #AIagents to interact with large APIs with minimal token usage.

    The server reduces context footprint across 2,500+ endpoints, improves multi-API orchestration, and provides a secure, code-centric execution environment for LLM agents.

    Deep dive on #InfoQbit.ly/4dTJgqQ

    #SoftwareArchitecture #LLMs #API

  16. Cloudflare’s new (MCP) server powered by Code Mode enables to interact with large APIs with minimal token usage.

    The server reduces context footprint across 2,500+ endpoints, improves multi-API orchestration, and provides a secure, code-centric execution environment for LLM agents.

    Deep dive on bit.ly/4dTJgqQ

  17. @infoq Great case study. Central registry + human-in-the-loop approvals are exactly the right building blocks.

    We see the same pattern with ToolMesh: a gateway between agent and API. Instead of building an MCP server per API, a YAML file describes the endpoints — ToolMesh handles ACL, credential isolation, and audit trails.

    Pinterest's approach shows MCP works in production — when the governance layer is right.

    toolmesh.io

    #ModelContextProtocol #AIAgents #OpenSource

  18. @infoq Great case study. Central registry + human-in-the-loop approvals are exactly the right building blocks.

    We see the same pattern with ToolMesh: a gateway between agent and API. Instead of building an MCP server per API, a YAML file describes the endpoints — ToolMesh handles ACL, credential isolation, and audit trails.

    Pinterest's approach shows MCP works in production — when the governance layer is right.

    toolmesh.io

    #ModelContextProtocol #AIAgents #OpenSource

  19. @infoq Great case study. Central registry + human-in-the-loop approvals are exactly the right building blocks.

    We see the same pattern with ToolMesh: a gateway between agent and API. Instead of building an MCP server per API, a YAML file describes the endpoints — ToolMesh handles ACL, credential isolation, and audit trails.

    Pinterest's approach shows MCP works in production — when the governance layer is right.

    toolmesh.io

    #ModelContextProtocol #AIAgents #OpenSource

  20. @infoq Great case study. Central registry + human-in-the-loop approvals are exactly the right building blocks.

    We see the same pattern with ToolMesh: a gateway between agent and API. Instead of building an MCP server per API, a YAML file describes the endpoints — ToolMesh handles ACL, credential isolation, and audit trails.

    Pinterest's approach shows MCP works in production — when the governance layer is right.

    toolmesh.io

    #ModelContextProtocol #AIAgents #OpenSource

  21. @infoq Great case study. Central registry + human-in-the-loop approvals are exactly the right building blocks.

    We see the same pattern with ToolMesh: a gateway between agent and API. Instead of building an MCP server per API, a YAML file describes the endpoints — ToolMesh handles ACL, credential isolation, and audit trails.

    Pinterest's approach shows MCP works in production — when the governance layer is right.

    toolmesh.io

    #ModelContextProtocol #AIAgents #OpenSource

  22. #Pinterest has deployed a production-ready #ModelContextProtocol (#MCP) ecosystem, enabling #AIagents to automate complex engineering tasks and integrate internal tools.

    Domain-specific MCP servers + central registry + human-in-the-loop approvals ⇒ boost security, governance & productivity - saving thousands of hours monthly.

    🔗 Details: bit.ly/4dVIhX6

    #InfoQ #SoftwareArchitecture

  23. #Pinterest has deployed a production-ready #ModelContextProtocol (#MCP) ecosystem, enabling #AIagents to automate complex engineering tasks and integrate internal tools.

    Domain-specific MCP servers + central registry + human-in-the-loop approvals ⇒ boost security, governance & productivity - saving thousands of hours monthly.

    🔗 Details: bit.ly/4dVIhX6

    #InfoQ #SoftwareArchitecture

  24. #Pinterest has deployed a production-ready #ModelContextProtocol (#MCP) ecosystem, enabling #AIagents to automate complex engineering tasks and integrate internal tools.

    Domain-specific MCP servers + central registry + human-in-the-loop approvals ⇒ boost security, governance & productivity - saving thousands of hours monthly.

    🔗 Details: bit.ly/4dVIhX6

    #InfoQ #SoftwareArchitecture

  25. #Pinterest has deployed a production-ready #ModelContextProtocol (#MCP) ecosystem, enabling #AIagents to automate complex engineering tasks and integrate internal tools.

    Domain-specific MCP servers + central registry + human-in-the-loop approvals ⇒ boost security, governance & productivity - saving thousands of hours monthly.

    🔗 Details: bit.ly/4dVIhX6

    #InfoQ #SoftwareArchitecture

  26. has deployed a production-ready () ecosystem, enabling to automate complex engineering tasks and integrate internal tools.

    Domain-specific MCP servers + central registry + human-in-the-loop approvals ⇒ boost security, governance & productivity - saving thousands of hours monthly.

    🔗 Details: bit.ly/4dVIhX6

  27. What happens when a major financial institution prepares its #APIs for #AIagents?

    #MorganStanley had to rethink large parts of its API program.

    The big shift: #ModelContextProtocol (MCP) - which has gone from obscurity to industry standard in ~18 months.

    It fundamentally changes who - or what - is consuming your APIs.

    Learn more: bit.ly/3PFnUmV

    #InfoQ

  28. What happens when a major financial institution prepares its #APIs for #AIagents?

    #MorganStanley had to rethink large parts of its API program.

    The big shift: #ModelContextProtocol (MCP) - which has gone from obscurity to industry standard in ~18 months.

    It fundamentally changes who - or what - is consuming your APIs.

    Learn more: bit.ly/3PFnUmV

    #InfoQ

  29. What happens when a major financial institution prepares its #APIs for #AIagents?

    #MorganStanley had to rethink large parts of its API program.

    The big shift: #ModelContextProtocol (MCP) - which has gone from obscurity to industry standard in ~18 months.

    It fundamentally changes who - or what - is consuming your APIs.

    Learn more: bit.ly/3PFnUmV

    #InfoQ

  30. What happens when a major financial institution prepares its #APIs for #AIagents?

    #MorganStanley had to rethink large parts of its API program.

    The big shift: #ModelContextProtocol (MCP) - which has gone from obscurity to industry standard in ~18 months.

    It fundamentally changes who - or what - is consuming your APIs.

    Learn more: bit.ly/3PFnUmV

    #InfoQ