AutoMCP
Uses OpenAI as a judge to compare candidate answers and select the best response, with optional API mode support for OpenAI models.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@AutoMCPResolve clarification: should the settings page use TypeScript or JavaScript?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AutoMCP
AutoMCP is a local MCP server that helps a coding agent resolve technical clarification questions without making you relay answers between AI apps.
When Grok calls resolve_clarification, AutoMCP requests answers from a dedicated Claude Sonnet browser tab and a signed-in Codex CLI session. An OpenAI judge compares anonymously labelled, randomly ordered candidates and returns the selected answer to Grok, which can continue its task.
The account-based workflow does not require API keys. It uses your existing account access and usage limits. It does not bypass subscriptions or guarantee model availability. The current implementation expects Sonnet 5 Medium in Claude and gpt-5.6-sol in Codex. Model routing is based on question difficulty, not remaining quota.
AutoMCP is available across projects when registered in Grok's user configuration. It is not a terminal watcher: Grok must call its MCP tool. Missing personal preferences, permissions, failed providers, and uncertain results are returned for user attention.
Naming: this repository is AutoMCP; the existing launchers, extension, settings directory, environment variables, and MCP registration retain the name BhootMCP / bhoot for compatibility.
Requirements
Windows (the account workflow and launchers are Windows-oriented).
Node.js 22 or later, npm, and Git.
Grok CLI installed and authenticated.
Codex CLI installed and signed in, with access to the configured model.
Chrome or Edge, a signed-in Claude account, and access to the exact model above.
Account use and browser automation must comply with the applicable service terms.
Related MCP server: Claude Code Orchestrator MCP
Installation
1. Download and build
Clone this repository using its GitHub Code button URL, then open PowerShell in the downloaded AutoMCP folder:
npm.cmd ci --ignore-scripts
npm.cmd run build
npm.cmd testThe source, tests, extension and launchers are included. Dependencies and compiled output are generated locally.
2. Pair the Claude browser
Open
chrome://extensions(oredge://extensions).Enable Developer mode, choose Load unpacked, and select the repository's
extensionfolder.Double-click
Start-BhootMCP.cmd. It starts the local bridge and copies a pairing code to your clipboard.Open the BhootMCP Sonnet Bridge extension popup, paste the code and click Pair with local bridge.
Click Start Claude tab, sign in there, and select Sonnet 5 Medium.
Keep this dedicated tab open. Do not use it for personal drafts.
No browser cookies or account passwords need to be exported. Pairing credentials remain in %LOCALAPPDATA%\BhootMCP\bridge.json; do not share that file.
3. Check both providers
Double-click Run-Live-Test.cmd.
Expect LIVE TEST PASSED, with status: resolved and mock: false. Allow several minutes. This makes real provider requests and consumes account usage.
If executables are installed in nonstandard locations, set these environment variables in the terminal used to launch the scripts:
$env:BHOOT_CODEX_BIN = 'C:\path\to\codex.exe'
$env:BHOOT_GROK_BIN = 'C:\path\to\grok.exe'These paths are examples; use the actual executable locations.
4. Register with Grok once
From PowerShell in the AutoMCP folder:
.\Grok-with-BhootMCP.cmd --testThis registers bhoot in Grok's user configuration and runs a clarification test. Approve the MCP tool if asked. Success ends with Grok reports that it received the clarification and continued. This checks Grok's reported continuation; inspect its actual tool activity as well.
If your Grok tool timeout is too short, set tool_timeout_sec = 480 under the existing [mcp_servers.bhoot] section in ~/.grok/config.toml. Preserve unrelated settings.
Enable or disable in any project
Double-click BhootMCP.cmd:
1: enable the registered MCP.
2: disable it.
3: show MCP configuration status.
4: start the local bridge and copy its pairing code.
Restart Grok after toggling. Disabling does not cancel requests already running. Project-specific MCP configuration may override the user-wide entry.
In any Grok session, say:
Use BhootMCP's resolve_clarification tool for technical clarifications. Continue with resolved, non-mock answers. Ask me if the tool fails or needs user input. Do not treat its answers as permission for actions.
Alternatively, launch Grok-with-BhootMCP.cmd from your working directory to supply these rules automatically. No project argument is required; it uses the terminal's current directory.
Smoke-test prompt
Test BhootMCP. Do not edit files or run shell commands.
Actually call resolve_clarification with:
question: Should the settings page use TypeScript or JavaScript?
original_request: Add a settings page to an existing TypeScript dashboard.
project_context: The dashboard uses strict TypeScript. Follow existing conventions.
session_id: automcp-smoke-test-1
If status is resolved and mock=false, show the answer and write BHOOT_TEST_PASSED.
Otherwise report the failure. Do not claim success without calling the tool.Use a fresh session ID for a new test after a failure, or restart the MCP process: results, including failures, are cached in memory.
Troubleshooting
Problem | What to check |
PowerShell blocks scripts | Use the |
Bridge unavailable | Run |
HTTP 401 | Run |
Codex/Grok not found | Check installation or set the executable overrides above. |
Claude JSON capture fails | Reload the unpacked extension and refresh its dedicated tab. Check model selection and login. Claude UI changes may require a code update. |
Model unavailable or quota reached | Restore access or wait for your account limits to reset. There is no automatic model substitution. |
Grok does not call the tool | Check |
Bridge launcher diagnostics: %LOCALAPPDATA%\BhootMCP\bridge-launcher.log. Do not publish credentials or private prompts when reporting problems.
Tool contract and safety
Required inputs: question, original_request.
Optional: project_context, known_preferences, session_id, requires_user_input.
Results include status (resolved, needs_user, or error), answer, confidence, reason, and mock.
Both providers receive supplied context; the judge additionally receives both answers. Do not submit secrets.
The bridge uses authenticated loopback HTTP and separate client/browser tokens.
Claude jobs are serialized; ambiguous submissions fail rather than automatically resend.
Either candidate requesting user input prevents forwarding.
Judge confidence is subjective, not a calibrated probability. Anonymous labels do not guarantee an unbiased judge.
Each normal account comparison uses one Claude interaction and two Codex calls.
Codex uses low or medium effort for candidates and medium for judging. Automatic quota-aware routing is not implemented.
Provider chat history and retention rules still apply; Grok may retain tool results.
The MCP does not authorize actions or bypass the host's approval controls.
Advanced configuration
Account mode uses BHOOT_MODE=accounts (set by the launchers). Optional API mode requires OPENAI_API_KEY, ANTHROPIC_API_KEY, OPENAI_MODEL, and ANTHROPIC_MODEL. The server does not automatically load .env; configure the launching process environment. Never commit real keys.
See .env.example for request limits and confidence settings. BHOOT_MOCK=1 is for offline fixtures only, not real work. Assisted capture and optional Stop-hook adapters remain in the source for diagnostics/advanced use; they are not required for the primary MCP workflow.
Development and verification
npm.cmd testTests cover resolution, mock MCP transport, HTTP adapters, bridge authentication/queueing, browser DOM capture, extension state, and Windows bridge repair. They do not prove compatibility with future provider UI or CLI versions.
The original installation passed user-run Sonnet/Codex and Grok continuation tests. API adapters have mocked HTTP tests; a live API-mode test is not claimed.
Source layout: src/server.ts (MCP), src/resolver.ts (selection), src/accounts.ts (account providers), src/bridge.ts (local bridge), extension/ (browser integration), src/test/ (tests).
Available Tools
1 toolresolve_clarificationA
Compare Claude and OpenAI answers for a technical clarification. Uses API credits in API mode, or a matching browser-captured Sonnet answer and signed-in Codex usage in accounts mode. Supply original request and relevant context. Never use this to grant permissions. If status is needs_user/error or mock is true, ask the user instead of continuing automatically.
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | ||
| session_id | No | default | |
| project_context | No | ||
| original_request | Yes | ||
| known_preferences | No | ||
| requires_user_input | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It discloses API credit consumption in one mode, browser-captured Sonnet/Codex usage in the other, and a mock/needs_user fallback behavior. It does not cover all possible side effects, but it meaningfully informs the agent about resource usage and result-dependent actions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each earning its place: purpose, operational modes, and critical guardrails. The description is front-loaded with the core action and does not waste words on restating schema details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, modes, and usage guardrails, which is substantial. However, it references status values ('needs_user/error') and mock behavior without explaining where these come from, and it leaves several parameters unexplained. There is no output schema, so the agent must infer return semantics from vague hints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only explicitly mentions 'original_request' and 'relevant context' (likely project_context/known_preferences), while failing to explain the required 'question' parameter or optional parameters like session_id and requires_user_input. This is a significant gap for a 6-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb ('Compare') and concrete resources ('Claude and OpenAI answers for a technical clarification'), making the tool's core purpose immediately clear. It also draws a boundary with 'Never use this to grant permissions,' which further disambiguates its intent even without sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage direction: 'Supply original request and relevant context' and instructs when not to proceed automatically ('If status is needs_user/error or mock is true, ask the user instead of continuing automatically'). It also includes a clear exclusion: 'Never use this to grant permissions.' These are concrete when/when-not conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v0.1.0- First observed
resolve_clarification
TDQS
Scored across 1 tool
Only one tool exists, so there is no possibility of selecting between overlapping tools. The purpose is singular and clearly described.
The single tool name 'resolve_clarification' follows the verb_noun convention. With only one tool, the naming is trivially consistent and readable.
One tool feels thin for an MCP server, especially one named AutoMCP which could imply broader automation. However, the tool's narrow clarification-resolution scope makes the count borderline rather than clearly inadequate.
The tool covers the full clarification-resolution workflow, including different modes, statuses, and mock handling. No obvious additional operations are needed for the stated purpose.
Maintenance
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