"How to make API calls in code" matching MCP servers:

Provides persistent, searchable memory across AI coding agent and chat history (Claude Code, Codex, Gemini CLI, ChatGPT, and more) via retrieval-augmented generation, enabling semantic and hybrid search to retain context across sessions.

MCP server for the Cloudflare API v4, written in Go. Exposes 28 read tools across zones, DNS, WAF/firewall, rate limits, HTTP request logs, Security Center, and threat intelligence.

Figma MCP server with full read/write access via plugin bridge — no API token, no rate limits. 58 tools for design automation: styles, variables, components, prototypes, and content.

A TypeScript server implementing the Model Context Protocol that provides secure code execution in isolated Docker containers, allowing LLM applications to safely run Python, Go, or JavaScript code snippets.

Enables coding agents to develop on one machine and verify results on another, using branch-bound runbooks, isolated checkpoints, and structured receipts to guide repair iterations.

Enables AI agents to query cluster-wide network traffic, investigate API calls, and perform root cause analysis using natural language, with access to decrypted TLS traffic and Kubernetes context.

Execute code in 8 programming languages via gVisor-sandboxed Docker containers. Supports Python, JS, TS, Go, Java, C++, C, and Bash.

MCP gateway for GREEN-API WhatsApp that lets AI agents send messages, manage instances, and receive notifications via WhatsApp using the Model Context Protocol.

An MCP bridge that lets Codex and Claude Code interact with OpenLinker agents, and allows the host to serve as a callable agent in the OpenLinker network.

This project implements a simple MCP server in Go that exposes a single tool (create_short_link) to generate short URLs using the Rebrandly API.

RegressGuard is an MCP server that records a known-good baseline and lets AI coding agents detect regressions (broken API contracts, failing tests, schema changes) during their edit loop, allowing them to self-correct before committing.

Provides git-aware safe file operations, allowing AI agents to delete files while protecting git-tracked source code from accidental deletion.

A self-hosted MCP server that provides capability packs for AI agents to perform browser, desktop, git, and code actions via schema-validated JSON calls, enabling reliable agentic workflows even with small open-weight models.

Connect your Umami Analytics to any MCP client to derive insights from natural language.

An MCP server to create secure code sandbox environment for executing code within Docker containers.

Enables MCP-capable agents to join Landfall incident war rooms as live investigators, contributing findings and widgets to the incident timeline in realtime while pulling other investigators' discoveries, with single-use share links or authenticated sessions.

A local MCP server that indexes codebases into Neo4j and provides tools for code analysis, dependency visualization, and impact assessment.

This project is intended as a both MCP server connecting to Kubernetes and a library to build more servers for any custom resources in Kubernetes.

LLM Optimizer is an AI visibility intelligence platform. It analyzes how large language models and AI search engines perceive, cite, and recommend brands; then provides research-backed optimization strategies to improve that visibility.

Source-code intelligence for agents, powered by OpenGrok and Go.