Which integrations are available for this server?

Provides diagnostics for FiveM servers by scanning server.cfg, resource manifests, and logs to identify issues such as missing resources, malformed manifests, and common configuration errors, with the ability to propose and apply low-risk fixes.

How do I use fivem-server-doctor-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@fivem-server-doctor-mcp diagnose why my FiveM server won't start" 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.

fivem-server-doctor-mcp

by mkcrw

Overview Schema Related Servers Score Discussions

TypeScript

Local

FiveM Server Doctor MCP

Local MCP server for Claude Desktop, Codex, and other MCP clients that answers one question:

Why is my FiveM server or resource broken?

fivem-server-doctor-mcp reads local txAdmin/FiveM files over stdio, scans server.cfg, resource folders, manifests, and recent logs, then returns ranked findings with exact evidence. It can propose narrow text-file fixes and can apply only generated low-risk fixes when writes are explicitly enabled.

Maintained by FiveMX. Sponsor link: fivemx.com.

What It Detects

Missing resource folders referenced by ensure or start.
Resource folders missing fxmanifest.lua or __resource.lua.
Common fxmanifest.lua problems: missing fx_version, missing game, missing listed files, missing dependencies.
txAdmin/FiveM log patterns: missing resources, malformed manifests, missing dependency hints, port bind failures, missing license keys, database connection hints, yarn/webpack/module install errors.
Secrets in output are masked, including license keys, DB URLs/passwords, tokens, and connection strings.

The scanner parses manifests as text. It never executes Lua from a resource.

Related MCP server: TaskBounty Check

Install

pnpm add -g fivem-server-doctor-mcp

Or run it without a global install:

npx -y fivem-server-doctor-mcp --server-cfg /path/to/server.cfg --resources /path/to/resources

CLI Options

fivem-server-doctor-mcp \
  --txdata /path/to/txData/default \
  --server-cfg /path/to/server.cfg \
  --resources /path/to/resources

Optional txAdmin status check:

TXHOST_API_TOKEN=... fivem-server-doctor-mcp \
  --txadmin-url http://127.0.0.1:40120 \
  --txadmin-token-env TXHOST_API_TOKEN

Writes are disabled by default. Enable generated low-risk patch application only for the launched process:

FIVEM_DOCTOR_ALLOW_WRITE=1 fivem-server-doctor-mcp --server-cfg ./server.cfg --resources ./resources

Codex Setup

codex mcp add fivem-doctor -- npx -y fivem-server-doctor-mcp \
  --server-cfg /path/to/server.cfg \
  --resources /path/to/resources \
  --txdata /path/to/txData/default

Then ask Codex:

Use fivem-doctor to run doctor_scan and explain why my FiveM server is not starting.

Claude Desktop Setup

Add this to your Claude Desktop MCP config:

{
  "mcpServers": {
    "fivem-doctor": {
      "command": "npx",
      "args": [
        "-y",
        "fivem-server-doctor-mcp",
        "--server-cfg",
        "/path/to/server.cfg",
        "--resources",
        "/path/to/resources",
        "--txdata",
        "/path/to/txData/default"
      ]
    }
  }
}

For write-enabled local patching, add an env block:

{
  "mcpServers": {
    "fivem-doctor": {
      "command": "npx",
      "args": ["-y", "fivem-server-doctor-mcp", "--server-cfg", "/path/to/server.cfg", "--resources", "/path/to/resources"],
      "env": {
        "FIVEM_DOCTOR_ALLOW_WRITE": "1"
      }
    }
  }
}

MCP Interface

Tools:

doctor_scan: scans configured status, logs, server.cfg, resources, and manifests.
resource_inspect: inspects one resource folder and manifest.
propose_fixes: returns generated fix candidates.
apply_fix: applies one generated fix only when writes are enabled, the target hash matches, the path is under configured roots, and the fix risk is low.

Resources:

fivem://status
fivem://server-cfg
fivem://logs/recent
fivem://resources
fivem://resources/{name}/manifest

Prompts:

diagnose_fivem_startup
review_new_resource_install
explain_txadmin_log_error

Safety Model

No private txAdmin UI scraping.
No browser sessions, cookies, or CSRF-protected routes.
No RCON, restart, stop, ban, or live server control tools in v1.
No arbitrary file writes.
apply_fix only writes generated low-risk changes for server.cfg, fxmanifest.lua, or __resource.lua style text fixes under configured roots.
Existing files are backed up into .fivem-doctor-backups/ before replacement.

Development

pnpm install
pnpm build
pnpm test

The test suite uses fixture-based node:test coverage and starts a real stdio MCP client against the built server.

Docs

License

MIT

Available Tools

4 tools

apply_fixApply Generated FixA

Applies one generated low-risk fix only when writes are enabled, the file hash still matches, and the target path is under a configured root.

ParametersJSON Schema

Name	Required	Description	Default
`fixId`	Yes
`expectedHash`	No

TDQS

A4/5.0

Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It reveals that this is a write operation with safety checks (writes enabled, hash match, root path), implying it will not apply under other conditions. However, it does not explicitly state failure modes, reversibility, or what happens if checks fail.

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, well-structured sentence that front-loads the core action and key conditions. It is concise with no unnecessary words.

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

Completeness3/5

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

Given two parameters, no output schema, and no annotations, the description provides a high-level overview but omits critical operational details like what fixId refers to, the expectedHash parameter's role, and potential return values. It is adequate as a starting point but not fully complete for an agent to invoke the tool confidently.

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

Parameters2/5

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

The input schema has zero description coverage, and the description does not explain either parameter. It mentions 'file hash still matches' which loosely relates to expectedHash, but fixId is never explained. This leaves the agent guessing about parameter purpose and format.

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 the tool applies a generated low-risk fix, using a specific verb ('applies') and resource ('generated fix'). It distinguishes itself from siblings like propose_fixes by indicating this is the execution step, not the proposal step.

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

Usage Guidelines4/5

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

The description explicitly provides conditions for use: 'only when writes are enabled, the file hash still matches, and the target path is under a configured root.' This gives clear guidance on when the tool can be used, though it does not explicitly name alternatives or when not to use it beyond these conditions.

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

doctor_scanRun FiveM Server Doctor ScanA

Scans txAdmin status/logs, server.cfg, resources, manifests, dependencies, and returns ranked findings.

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

A3.7/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only mentions scanning and returning ranked findings, but does not state whether the operation is read-only, what permissions are needed, or how the findings are structured. This leaves significant unknowns for an agent.

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, concise sentence that front-loads the action, scope, and result. Every word adds value, with no redundancy or filler.

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

Completeness3/5

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

For a zero-parameter tool without an output schema, the description provides a good high-level overview but lacks details about the return value (e.g., what constitutes 'ranked findings' or severity levels). It also omits any prerequisites or environment context. This leaves the description moderately complete but with gaps.

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

Parameters4/5

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

The tool has zero parameters, so the description does not need to elaborate on parameter usage. The baseline of 4 applies for no-parameter tools, and the description correctly provides no parameter-related information that would be redundant or missing.

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 the tool's action ('scans') and lists the specific targets (txAdmin status/logs, server.cfg, resources, manifests, dependencies) along with the outcome ('returns ranked findings'). This distinguishes it from siblings like resource_inspect, which focuses on individual resources.

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

Usage Guidelines3/5

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

The description implies a comprehensive diagnostic scan but does not explicitly state when to use this tool versus alternatives. There are no usage exclusions or mentions of when to prefer resource_inspect or propose_fixes. The context is clear from the title and scope, but not spelled out.

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

propose_fixesPropose Safe Text FixesA

Returns exact low-risk fix candidates generated from the current scan.

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

A3.5/5.0

Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It does not explicitly state that the operation is read-only (though 'returns' implies it), nor does it explain prerequisites like requiring a prior scan or any side effects, leaving the agent with ambiguity.

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 sentence, front-loaded with the verb, and every word earns its place. There is no redundancy or wasted language.

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

Completeness3/5

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

The description is adequate for a simple, parameterless tool, but it leaves gaps: it doesn't define what constitutes a 'current scan', doesn't describe the structure of returned fix candidates, and doesn't connect to the apply_fix sibling workflow. Given the absence of an output schema and annotations, this is a notable gap.

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

Parameters4/5

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

The schema has zero parameters, so coverage is trivially 100%, but the baseline is 4. The description adds meaningful context by mentioning 'current scan', indicating that the tool relies on the scan context rather than explicit arguments, which is valuable beyond the empty schema.

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 that the tool returns exact low-risk fix candidates from the current scan, using the specific verb 'returns' and a distinct resource. It differentiates from siblings like apply_fix by focusing on proposal/generation rather than application.

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?

No guidance is provided on when to use this tool versus its siblings. The mention of 'current scan' implies a prerequisite but does not explicitly say to use it after doctor_scan and before apply_fix, nor does it mention any alternatives or exclusions.

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

resource_inspectInspect FiveM ResourceA

Inspects one resource folder, manifest, dependencies, and related file evidence.

ParametersJSON Schema

Name	Required	Description	Default
`name`	Yes	Resource folder name, for example oxmysql.

TDQS

A3.7/5.0

Behavior3/5

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

With no annotations, the description carries a heavier burden. The verb 'inspects' implies read-only, but the description does not explicitly state that nothing is modified, nor does it mention return formats, error behavior, or permissions. It adds some context by listing what is inspected (manifest, dependencies, file evidence) but stops short of full transparency.

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, tightly worded sentence that gets straight to the point. Every word contributes meaning, with no filler or redundancy. It is appropriately sized for a simple tool.

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

Completeness3/5

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

The tool is simple (1 parameter, no output schema, no annotations), but the description could be more complete. It lists what it inspects but does not explain the nature of the returned evidence or that the operation is read-only. Without an output schema, the agent relies on the description to set expectations for results, which is somewhat vague.

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?

Schema description coverage is 100% with a clear description of the 'name' parameter ('Resource folder name, for example oxmysql'). The tool description adds little beyond the schema, only reiterating 'one resource folder' which is already implied by the singular parameter. Baseline 3 applies.

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 the tool 'inspects one resource folder' and specifies what it covers: manifest, dependencies, and related file evidence. This specific verb+resource+scope distinguishes it from siblings like doctor_scan (broader scan), propose_fixes, and apply_fix.

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

Usage Guidelines3/5

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

The description implies usage for detailed inspection of a specific resource, but it does not explicitly state when to use this tool versus alternatives. It lacks explicit 'when' or 'when-not' guidance, relying on the tool name and sibling context to convey its niche.

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. Dates show when Glama detected each change.

4 tool updatesv0.1.0Aug 2, 2026
- First observedapply_fix
- First observeddoctor_scan
- First observedpropose_fixes
- First observedresource_inspect

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A3.8/5.0

Disambiguation5/5

Each tool has a distinct responsibility: scanning the whole server, inspecting a specific resource, proposing fixes, and applying a single fix. There is no overlap or ambiguity in their purposes.

Naming Consistency3/5

Tool names use a two-word underscore pattern, but the verb/noun order is inconsistent: doctor_scan and resource_inspect are object-first, while propose_fixes and apply_fix are verb-first. This mix is still readable but not perfectly predictable.

Tool Count5/5

Four tools form a tight, well-scoped workflow for diagnosing and fixing FiveM servers. Each tool adds a necessary stage in the process, and there is no bloat.

Completeness4/5

The scan → inspect → propose → apply lifecycle is complete for the core server-doctor functionality. A minor gap is the lack of a revert or validation step after applying a fix, but it can be worked around.

Maintenance

ActivitySlowing

ResponsivenessNo issues

Resources

GitHub Repository

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