Cursor Agent MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| cursor_agent_chatC | Chat with cursor-agent using a prompt and optional model/force/output_format. |
| cursor_agent_edit_fileC | Edit a file with an instruction. Prompt-based wrapper; no CLI subcommand required. |
| cursor_agent_analyze_filesC | Analyze one or more paths; optional prompt. Prompt-based wrapper. |
| cursor_agent_search_repoC | Search repository code with include/exclude patterns. Prompt-based wrapper. |
| cursor_agent_plan_taskC | Generate a plan for a goal with optional constraints. Prompt-based wrapper. |
| cursor_agent_rawC | Advanced: provide raw argv array to pass after common flags (e.g., ["search","--query","foo"]). |
| cursor_agent_runC | Run cursor-agent with a prompt and desired output format (legacy single-shot). |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 7 tools
The tools have some distinct purposes like analyze_files, edit_file, plan_task, and search_repo, but there is notable overlap between cursor_agent_chat and cursor_agent_run (both involve prompting the agent), and cursor_agent_raw is ambiguous as it could duplicate functionality of other tools. Descriptions help differentiate, but an agent might struggle to choose between chat and run for similar tasks.
All tool names follow a consistent snake_case pattern with the prefix 'cursor_agent_' followed by a verb or action (e.g., analyze_files, chat, edit_file). This uniformity makes the set predictable and easy to parse, with no deviations in style or structure.
With 7 tools, the count is reasonable for a server focused on interacting with a cursor-agent, covering analysis, chatting, editing, planning, raw execution, running, and searching. It's slightly lean but well-scoped, as each tool addresses a specific aspect of agent interaction without obvious bloat.
The tool surface covers key operations like analysis, chatting, editing, planning, and searching, but there are gaps in lifecycle coverage—for example, no tools for managing agent sessions, handling errors, or providing feedback on previous actions. The domain is prompt-based agent interaction, and while core workflows are present, the set lacks comprehensive support for advanced or iterative tasks.