"MCP servers for curated context in Cursor IDE to plan, debug, and iterate on features" matching MCP servers:

Cross-platform MCP server providing Claude Code-style plan mode via four tools (enter_plan_mode, get_plan_mode_standards, todo_write, exit_plan_mode) with soft guidance through SKILL.md.

A FastMCP server for Cursor platform APIs enabling spend guardrails, cloud agent monitoring, and inter-agent inbox messaging.

Serves Claude Desktop a unified, actionable read of Google Calendar and Google Tasks, surfacing overdue items first, then the day's events, free slots, and open tasks, with explicit-request-only write tools for creating, updating, completing, and deleting. Google stays the sole source of truth with no server-side storage beyond the OAuth token and a 30-second read cache.

Enables interactive feedback with image support in Cursor, allowing users to paste images for visual context and feedback.

A smart debugging agent that remembers errors, automatically diagnoses issues, and accumulates solutions for faster resolution.

Enables progress-triggered text-to-speech in Cursor Agent, with speak and stop controls and voice matching the system UI language.

Enables systematic investigation of VMware errors and events by correlating event timelines, ranking root-cause hypotheses, and suggesting next diagnostic steps.

An MCP server that lets AI agents drive real Android apps on emulators/devices, returning screen state, logs, and screenshots after every action, and learns a navigation map of the app for efficient route-based interaction.

An MCP server that lets Claude spawn Cursor subagents as async, bounded workers, enabling non-blocking task delegation with asynchronous completion notifications.

Bridges web browsers and Claude Code for seamless debugging workflows by receiving debug data from browser widgets and exposing it to Claude Code via MCP protocol.

Enables AI tools to perform full-featured embedded microcontroller debugging via pyOCD and CMSIS-DAP probes, including probe management, flashing, breakpoints, register/memory access, fault analysis, and RTT communication.

Generates multi-day CKD meal plans for children based on PRNT targets (energy, protein, potassium, phosphorus, sodium), providing nutrient summaries and target achievement rates for dietitians.

This MCP server generates individualized meal plans for children with chronic kidney disease (CKD) based on KDIGO 2024/PRNT 2020/KRCP 2025 guidelines, incorporating patient age, CKD stage, allergies, dietary culture, and diet diary analysis. It provides deterministic nutrient computations and tools for meal plan generation, food database lookup, and risk analysis.

Provides GDB and clangd-based tools for debugging C++ programs, enabling step execution, variable inspection, diagnostics, and combined runtime-static analysis.

Provides AI agents with Roku BrightScript debugging tools, including log reading, scene graph inspection, breakpoint management, variable inspection, and execution control.

Enables AI agents to directly inspect and debug embedded hardware: reading/writing serial ports and bus devices, auto-detecting baud rates, parsing Modbus/NMEA/custom binary frames, plus diagnosing failures through a 45-rule fault-pattern library, error-code tables, and compile/flash error translation. Also provides pin-conflict checking, register and Cortex-M fault decoding, pre-validated driver and component selection libraries, board knowledge, and guarded flashing with post-flash byte-level verification.

Provides Codex and other MCP clients a local web debugging server that coordinates a browser session, JavaScript debugger, bounded runtime evidence, and reproducible flow verification for vanilla HTML/JS projects.

Enables MCP clients to delegate bounded tasks to an explicitly selected Cursor model with durable, restart-safe run state, idempotent runs, and fail-closed security defaults.

Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.

A minimal, secure MCP server for AI-assisted mobile development, enabling build, install, interact, and inspect Android/iOS apps.

Enables academic research through paper search across multiple databases (IACR, CryptoBib, Crossref, Google Scholar), PDF processing, and GitHub repository browsing. Features modular architecture with FastMCP-based proxy server routing to specialized academic tools.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

An MCP server that keeps raw tool output out of the context window by sandboxing and compressing results (about 98% reduction), persisting file edits, git operations, tasks and decisions in SQLite with BM25 retrieval so the agent resumes after compaction, and enforcing routing across 17 platforms via MCP and hooks. It also encourages the model to write scripts that compute answers and log only results instead of reading large data into context.

Multi-modal RAG engine for AI assistants. Stores conversation history, conclusions, diffs, error traces, and other development artifacts in LanceDB with vector search, multi-factor scoring, and an LLM-driven consolidation pipeline.

Context Mode is an MCP server that reduces context window waste by sandboxing data-heavy tools, tracking session state in SQLite, and promoting code-based analysis over raw data reads, achieving up to 98% context savings.

An MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programming languages and authenticated CLIs.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Provides official INDEC register designs and methodological rules to AI models, enabling accurate EPH data analysis code (R/Python) without hallucinations.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

A local-first MCP server that ingests PDFs, extracts structure, and provides semantic search and sequential navigation tools for AI clients to query and learn from documents.