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tuannvm

codex-mcp-server

by tuannvm

codex

Destructive

Execute coding tasks and receive AI-powered code analysis, generation, or review through Codex CLI. Configure model, reasoning effort, and sandbox policies for controlled execution.

Instructions

Execute Codex CLI in non-interactive mode for AI assistance

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesThe coding task, question, or analysis request
sessionIdNoOptional session ID for conversational context. Note: when resuming a session, sandbox/fullAuto/workingDirectory parameters are not applied (CLI limitation)
resetSessionNoReset the session history before processing this request
modelNoSpecify which model to use (defaults to gpt-5.3-codex). Options: gpt-5.3-codex, gpt-5.2-codex, gpt-5.1-codex, gpt-5.1-codex-max, gpt-5-codex, gpt-4o, gpt-4, o3, o4-mini
reasoningEffortNoControl reasoning depth (none < minimal < low < medium < high < xhigh)
sandboxNoSandbox policy for shell command execution. read-only: no writes allowed, workspace-write: writes only in workspace, danger-full-access: full system access (dangerous)
fullAutoNoEnable full-auto mode: sandboxed automatic execution without approval prompts (equivalent to -a on-request --sandbox workspace-write)
workingDirectoryNoWorking directory for the agent to use as its root (passed via -C flag)
callbackUriNoStatic MCP callback URI to pass to Codex via environment (if provided)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
threadIdNo
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate destructiveHint=true and readOnlyHint=false. The description adds 'non-interactive mode', which clarifies that the tool runs without user prompts, a behavioral trait not captured in annotations. This adds moderate value beyond what annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no extraneous information. It efficiently conveys the core purpose without waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite the tool's complexity (9 parameters, destructive hint, open world hint), the description is very brief and lacks details on side effects, return values, or usage scenarios. The openWorldHint suggests potential external impacts, but the description does not address this.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage with descriptions for all 9 parameters, so the baseline is 3. The description does not add any additional parameter meaning beyond what the schema already provides, thus a score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Execute Codex CLI in non-interactive mode for AI assistance', specifying the verb 'Execute' and the resource 'Codex CLI'. It distinguishes from sibling tools like 'help', 'listSessions', 'ping', 'review', and 'websearch' by focusing on code execution for AI-driven tasks.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives or when not to use it. It lacks explicit context for usage, such as prerequisites or exclusions, which is critical given the presence of sibling tools with overlapping purposes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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