Tags: model context protocol* + api*

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  1. Developers are replacing bloated MCP servers with Markdown skill files — cutting token costs by 100x. This article explores a two-layer architecture emerging in production AI systems, separating knowledge from execution. It details how skills (Markdown files) encode stable knowledge, while MCP servers handle runtime API interactions. The piece advocates for a layered approach to optimize context window usage, reduce costs, and improve agent reasoning by prioritizing knowledge representation in a version-controlled, accessible format.
  2. This guide walks you through building production-grade MCP servers that expose your organization's internal data to AI models, covering authentication, multi-tenancy, streaming, and deployment patterns.
  3. Google is announcing the public preview of the Developer Knowledge API and its associated Model Context Protocol (MCP) server. These tools provide a machine-readable gateway to Google’s official developer documentation, enabling AI assistants to access accurate and up-to-date information for building with Google technologies like Firebase, Android, and Google Cloud.
  4. Agoda engineers developed API Agent, a system with zero code and zero deployments that enables a single Model Context Protocol (MCP) server to connect to internal REST or GraphQL APIs. The system is designed to reduce the operational overhead of managing multiple APIs with distinct schemas and authentication methods, allowing teams to query services through AI assistants without building individual MCP servers for each API.
  5. This post breaks down why MCP servers fail, six best practices for building ones that work, and how Skills and MCP complement each other. It emphasizes designing MCP servers as user interfaces for AI agents, focusing on outcomes, flattened arguments, clear instructions, curation, discoverable naming, and pagination.

    * **Focus on Outcomes, Not Operations:** Instead of exposing granular API endpoints as tools, create high-level tools that deliver the *result* the agent needs.
    * **Flatten Arguments:** Use simple, typed arguments instead of complex nested structures.
    * **Instructions are Context:** Leverage docstrings and error messages to provide clear guidance to the agent.
    * **Curate Ruthlessly:** Limit the number of tools exposed and focus on essential functionality.
    * **Name Tools for Discovery:** Use a consistent naming convention (service_action_resource) to improve discoverability.
    * **Paginate Large Results:** Avoid overwhelming the agent with large datasets; use pagination with metadata.
    2026-01-23 Tags: , , , by klotz
  6. This article provides a comprehensive guide on implementing the Model Context Protocol (MCP) with Ollama and Llama 3, covering practical implementation steps and use cases.
  7. A Model Context Protocol (MCP) service that provides access to Ansible Automation Platform (AAP) APIs through OpenAPI specifications.
  8. This article compares Model Context Protocol (MCP), Function Calling, and OpenAPI Tools for integrating tools and resources with language models, outlining their strengths, limits, security considerations, and ideal use cases.
  9. The Universal Tool Calling Protocol (UTCP) is an open standard that describes how to call existing tools directly, eliminating the need for wrappers. It focuses on direct communication with tool endpoints (HTTP, gRPC, WebSocket, CLI, etc.) to reduce latency and maintain existing security and billing systems.
    2025-07-14 Tags: , , , , , , , by klotz
  10. This article lists and ranks the top Model Context Protocol (MCP) servers on GitHub as of June 2025, highlighting their capabilities and emphasizing the importance of security when granting agents access to sensitive data. It positions Pomerium as a solution for enforcing policy and securing agentic access to MCP servers.


    |**GitHub Repository** |**Description** |
    |---------------------------------|-----------------------------------------------------------------------------|
    | github/github-mcp-server | Manages GitHub issues, pull requests, discussions with identity & permissions. |
    | microsoft/playwright-mcp | Triggers browser automation tasks (QA, scraping, testing). |
    | awslabs/mcp | Exposes AWS documentation, billing data, and service metadata. |
    | hashicorp/terraform-mcp-server | Secure access to Terraform providers and modules. |
    | dbt-labs/dbt-mcp | Exposes dbt’s semantic layer and CLI commands. |
    | getsentry/sentry-mcp | Access to Sentry error tracking and performance telemetry. |
    | mongodb-js/mongodb-mcp-server | Interacts with MongoDB and Atlas instances securely. |
    | StarRocks/mcp-server-starrocks | Brings MCP to the StarRocks SQL engine. |
    | vantage-sh/vantage-mcp-server |Focuses on cloud cost visibility. |

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