Ein selbst gehostetes Gateway, das Codex-kompatible Agents und Tools über stabile API-Keys und automatisches Account-Routing verwaltet.
Auch bekannt als icoretech/codex-pooler
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Was ist Codex Pooler MCP?
Codex Pooler ist ein MCP server. Ein selbst gehostetes Gateway, das Codex-kompatible Agents und Tools über stabile API-Keys und automatisches Account-Routing verwaltet.
Zusammenfassung generiert aus dem README des Projekts
Über Codex Pooler MCP server
Das Verwalten mehrerer KI-Accounts und Tools über eine einzige Schnittstelle ist das, was codex-pooler für Entwickler und technische Teams ermöglicht. Dieses selbst gehostete Gateway fungiert als zentraler Hub für Codex-kompatible Agents und erlaubt es dir, Anfragen über stabile Pool API-Keys statt über einzelne Account-Credentials zu routen. Es unterstützt eine Vielzahl von Clients, darunter Cursor, Aider, Cline und verschiedene OpenAI-kompatible SDKs, was die Integration in bestehende Coding-Workflows erleichtert.
Betreiber können den Service mit Docker Compose oder Kubernetes deployen, um die Kontrolle über ihre eigene Infrastruktur zu behalten. Das System wählt automatisch den besten Upstream-Account basierend auf Model-Support, verfügbarer Quota und Account-Health aus. Es bietet fortgeschrittene Management-Features wie Request-Limits, tägliche oder wöchentliche Nutzungskontingente sowie ein Observatory-Dashboard zum Tracken von Aktivitäten und geschätzten Kosten. Da der Fokus auf reinen Metadaten-Operationen liegt, ermöglicht es Troubleshooting und Usage-Tracking, ohne sensible Gesprächsinhalte wie Prompts, Dateien oder Bilder zu speichern.
Was du damit machen kannst
- 1KI-Account-Management zentralisierenVerbinde mehrere Codex-Accounts mit einem einzigen Pool, um Kapazitäten und das Routing zu teilen, ohne die echten Credentials preiszugeben.
- 2Nutzungslimits für Teams erzwingenLege spezifische Request-Limits und zeitbasierte KI-Nutzungskontingente für verschiedene API-Keys fest.
- 3Stabile API-Verbindungen aufrechterhaltenNutze einen einzigen Pool API-Key, der unverändert bleibt, selbst wenn du zugrunde liegende Codex-Accounts hinzufügst oder ersetzt.
- 4Ressourcen-Health und Kosten überwachenBiete Nutzern ein persönliches Dashboard, um ihre eigene Aktivität, Antwortzeiten und Kosten einzusehen.
Geschrieben aus dem README des Projekts. Jeder Use Case wurde gegen ein Zitat daraus geprüft.
Konfiguration
CODEX_POOLER_API_KEYCODEX_POOLER_IMAGE_TAGOPENAI_API_KEYOPENAI_BASE_URLSTT_OPENAI_BASE_URL
| Name | Beschreibung | Typ |
|---|---|---|
| CODEX_POOLER_API_KEY | — | |
| CODEX_POOLER_IMAGE_TAG | — | |
| OPENAI_API_KEY | — | |
| OPENAI_BASE_URL | — | |
| STT_OPENAI_BASE_URL | — |
Automatisierte Checks
Geluften am 14. Nov. 2026Vollständiger Bericht →Noch nicht verifiziert. Ein Server benötigt einen Score von 80, keine kritischen Befunde und genug Daten für unsere Prüfung. Wie die Checks funktionieren
- Source Repository verknüpft und erreichbaricoretech/codex-pooler is public and reachablegithub.com/icoretech/codex-pooler ↗Bestanden
- Paket nennt dieses Repository als QuelleNicht geprüft
- Build-Herkunft (Sigstore-Attestierung)Nicht geprüft
- Open Source Lizenz (OSI)No licenseBefund
- Commit oder Release im letzten JahrLast commit or release 2026-11-14github.com/icoretech/codex-pooler ↗Bestanden
- OpenSSF ScorecardNicht geprüft
- Package-Name ähnelt keinem populären PackageNicht geprüft
- Kein kritischer Hinweis im Paket oder seinen AbhängigkeitenNicht geprüft
- Keine versteckten Anweisungen an das Modell0 tool descriptions and the README read; no override phrases, credential paths or hidden charactersBestanden
- Destruktive Tools sind markiertNicht geprüft
- Remote-Endpoint beantwortet den MCP-HandshakeNicht geprüft
README
Auf GitHub ansehenCodex Pooler is a self-hosted gateway for running Codex-compatible agents, tools, and automation through stable Pool API keys. It works with one upstream Codex account for credential isolation, client normalization, metadata-only operations, and saved reset visibility; add more accounts when you want shared capacity and routing across eligible accounts.
Clients send familiar Codex backend or OpenAI-compatible requests; Codex Pooler selects an eligible account based on model support, quota evidence, limits, session continuity, routing policy, and health. The Pool key stays stable while upstream assignments, lifecycle state, reset policy, and capacity change behind it.
Operators get one place to manage Pools, accounts, API keys, saved resets, routing, request accounting, audit logs, and health without storing prompts, files, audio, images, bearer tokens, or raw Codex secrets. Instance owners keep the global administration surface, while instance admins work only with their assigned Pools.
Highlights
- 🧩 Use the tools you already know: connect Codex, OpenCode and other supported coding agents, plus apps built with OpenAI-compatible SDKs
- 🔑 One key for your apps: connect tools with a Pool API key that stays the same when you add or replace Codex accounts, without sharing account credentials
- ⚡ High cache reuse across protocols: over 95% cached input observed on HTTP/SSE and WebSockets, backed by cache-aware routing and connection reuse
- 🎯 Automatic account selection: send requests to accounts that can serve the chosen model, with available quota and account health taken into account
- 📏 Control how much each key can use: set request limits and daily or weekly AI usage allowances
- 🚀 Give agents more room to work: let them use several tools at once in Full mode, with Lite compatibility when needed
- 🖼️ Images and voice, too: generate and edit images or transcribe audio through supported apps, using the same Pool API key
- 🛡️ Keep conversation content private: track usage and troubleshoot requests without saving prompts, replies, uploaded files, images or audio
- 🔁 Keep conversations together: keep supported sessions linked to the right account when a client reconnects
- 🔭 Let users track their own usage: enable a personal Observatory dashboard for each key, showing activity, response times and estimated costs
- 🏦 Put saved resets to use: see available reset credits and use them to restore account quota, manually or automatically when enabled
- 🖥️ Manage everything in one place: add accounts, manage keys and invites, check usage and change settings from a browser
- 👥 Organize teams and projects: group accounts into Pools with their own access rules and model choices
- 🤝 Connect accounts by invitation: let account owners join a Pool through a guided browser flow, without sending you credential files
- 🚨 Know when attention is needed: receive alerts about low capacity, account problems and reset events in the dashboard, by email or through webhooks
- 🔎 Spot model downgrades: see when the provider reports a different model from the one sent, or changes the model name during a response
- 🧷 Fill in missing continuity: derive stable session identities from cache keys or conversation IDs when a harness does not send them directly
- 🧱 Choose who can connect: optionally allow requests only from approved networks
- 🐳 Run it on your own infrastructure: start with Docker Compose or deploy on Kubernetes as your needs grow
Harness Configuration
Start with a running Codex Pooler instance, a Pool API key, and an installed
client. The examples include gpt-6-luna, gpt-6.1-sol and gpt-6-astra, with
Sol selected by default. Keep the models available to your Pool.
Replace <pool-api-key> with your key and run the command for your terminal
before starting the client.
macOS / Linux / Windows WSL (bash or zsh)
export CODEX_POOLER_API_KEY="<pool-api-key>"
Windows PowerShell
$env:CODEX_POOLER_API_KEY = "<pool-api-key>"
These commands set the key for the current terminal. For desktop apps, follow the linked guide to save the key for the app.
The paths below are defaults. On macOS/Linux, ~ is your home folder.
On Windows, paste paths starting with %USERPROFILE%, %APPDATA% or
%LOCALAPPDATA% into File Explorer's address bar. If you installed a client
inside WSL, use its Linux paths and commands inside WSL. Custom configuration
folders or profiles take precedence over these defaults.
For a local instance:
| Client | Base URL |
|---|---|
| Codex CLI / Desktop | http://localhost:4000/backend-api/codex |
| Other harnesses and SDKs | http://localhost:4000/v1 |
For a deployed instance, replace http://localhost:4000 with your instance's
host, such as https://codex-pooler.example.com. Merge snippets into existing
configurations. The examples use the large 828,400-token context for GPT-6.
Codex CLI and Desktop read the available context size automatically from your Pool.
Each entry covers the basic connection. Its full setup & extras link covers installation, advanced options and troubleshooting. Operator MCP is optional and uses a separate token; see Operator MCP Service.

| System | Configuration file |
|---|---|
| macOS / Linux | ~/.codex/config.toml |
| Windows | %USERPROFILE%\.codex\config.toml |
Open config.toml at the path for your system and add the following. If you
set CODEX_HOME, use the file in that folder instead. Keep name = "OpenAI"
to preserve Codex's native features. Catalog discovery is enabled by default;
model_catalog_url points it at your Pool.
model = "gpt-6.1-sol"
model_provider = "codex-pooler-ws"
[model_providers.codex-pooler-ws]
name = "OpenAI"
base_url = "http://localhost:4000/backend-api/codex"
model_catalog_url = "http://localhost:4000/backend-api/codex/models"
env_key = "CODEX_POOLER_API_KEY"
wire_api = "responses"
supports_websockets = true
requires_openai_auth = true
Restart Codex and choose a model available to your Pool. If you use Codex Desktop, follow the full guide to make your API key available to the app.
Full setup & extras — desktop setup, account settings, existing conversations and the optional custom provider name with its limitations.

| System | Configuration file |
|---|---|
| macOS / Linux | ~/.config/opencode/opencode.jsonc |
| Windows | %USERPROFILE%\.config\opencode\opencode.jsonc |
Open opencode.jsonc at the path for your system and add the configuration
for your OpenCode version below.
OpenCode v2
{
"$schema": "https://opencode.ai/config.json",
"model": "codex-pooler/gpt-6.1-sol",
"agents": {
"title": {
"model": "codex-pooler/gpt-6-luna"
}
},
"providers": {
"codex-pooler": {
"package": "@opencode/ai/providers/openai/responses",
"settings": {
"baseURL": "http://localhost:4000/v1",
"apiKey": "{env:CODEX_POOLER_API_KEY}",
"transport": "http",
"compaction": {
"type": "summary"
}
},
"models": {
"gpt-6-luna": {
"modelID": "gpt-6-luna",
"capabilities": {
"tools": true,
"input": ["text", "image"],
"output": ["text"]
},
"limit": { "context": 828400, "input": 828400, "output": 32000 },
"settings": {
"reasoningEffort": "high",
"reasoningSummary": "auto"
}
},
"gpt-6.1-sol": {
"modelID": "gpt-6.1-sol",
"capabilities": {
"tools": true,
"input": ["text", "image"],
"output": ["text"]
},
"limit": { "context": 828400, "input": 828400, "output": 32000 },
"settings": {
"reasoningEffort": "high",
"reasoningSummary": "auto"
}
},
"gpt-6-astra": {
"modelID": "gpt-6-astra",
"capabilities": {
"tools": true,
"input": ["text", "image"],
"output": ["text"]
},
"limit": { "context": 828400, "input": 828400, "output": 32000 },
"settings": {
"reasoningEffort": "high",
"reasoningSummary": "auto"
}
}
}
}
}
}
OpenCode v2 full setup & extras — installation and advanced options.
OpenCode v1
{
"$schema": "https://opencode.ai/config.json",
"model": "openai/gpt-6.1-sol",
"small_model": "openai/gpt-6-luna",
"provider": {
"openai": {
"npm": "@ai-sdk/openai",
"name": "Codex Pooler",
"options": {
"baseURL": "http://localhost:4000/v1",
"apiKey": "{env:CODEX_POOLER_API_KEY}"
},
"models": {
"gpt-6-luna": {
"id": "gpt-6-luna",
"name": "GPT-6 Luna",
"family": "gpt",
"attachment": true,
"reasoning": true,
"tool_call": true,
"temperature": false,
"options": {
"reasoningEffort": "high",
"reasoningSummary": "auto",
"include": ["reasoning.encrypted_content"]
},
"modalities": {
"input": ["text", "image"],
"output": ["text"]
},
"limit": { "context": 828400, "input": 828400, "output": 64000 }
},
"gpt-6.1-sol": {
"id": "gpt-6.1-sol",
"name": "GPT-6.1 Sol",
"family": "gpt",
"attachment": true,
"reasoning": true,
"tool_call": true,
"temperature": false,
"options": {
"reasoningEffort": "high",
"reasoningSummary": "auto",
"include": ["reasoning.encrypted_content"]
},
"modalities": {
"input": ["text", "image"],
"output": ["text"]
},
"limit": { "context": 828400, "input": 828400, "output": 64000 }
},
"gpt-6-astra": {
"id": "gpt-6-astra",
"name": "GPT-6 Astra",
"family": "gpt",
"attachment": true,
"reasoning": true,
"tool_call": true,
"temperature": false,
"options": {
"reasoningEffort": "high",
"reasoningSummary": "auto",
"include": ["reasoning.encrypted_content"]
},
"modalities": {
"input": ["text", "image"],
"output": ["text"]
},
"limit": { "context": 828400, "input": 828400, "output": 64000 }
}
}
}
}
}
OpenCode v1 full setup & extras — installation and OMO setup.

| System | Configuration file |
|---|---|
| macOS / Linux | ~/.openclaw/openclaw.json |
| Windows | %USERPROFILE%\.openclaw\openclaw.json |
Open openclaw.json at the path for your system and add this configuration:
{
agents: {
defaults: {
model: {
primary: "openai/gpt-6.1-sol",
list: [{ id: "background", model: "openai/gpt-6-luna" }],
},
compaction: { reserveTokens: 128000 },
},
},
models: {
mode: "merge",
providers: {
openai: {
baseUrl: "http://localhost:4000/v1",
apiKey: "${CODEX_POOLER_API_KEY}",
api: "openai-responses",
agentRuntime: { id: "openclaw" },
timeoutSeconds: 300,
models: [
{
id: "gpt-6-luna",
name: "GPT-6 Luna via Codex Pooler",
reasoning: true,
input: ["text", "image"],
contextWindow: 828400,
contextTokens: 828400,
maxTokens: 128000,
},
{
id: "gpt-6.1-sol",
name: "GPT-6.1 Sol via Codex Pooler",
reasoning: true,
input: ["text", "image"],
contextWindow: 828400,
contextTokens: 828400,
maxTokens: 128000,
},
{
id: "gpt-6-astra",
name: "GPT-6 Astra via Codex Pooler",
reasoning: true,
input: ["text", "image"],
contextWindow: 828400,
contextTokens: 828400,
maxTokens: 128000,
},
],
},
},
},
}
Restart OpenClaw and start a new conversation.
Full setup & extras — background tasks, more models and advanced options.

| System | Folder for .env and config.yaml |
|---|---|
| macOS / Linux | ~/.hermes/ |
| Windows | %LOCALAPPDATA%\hermes\ |
Open .env in the folder for your system and add your Pool API key and
Codex Pooler address. If you set HERMES_HOME, use that folder instead:
OPENAI_API_KEY=<pool-api-key>
OPENAI_BASE_URL=http://localhost:4000/v1
STT_OPENAI_BASE_URL=http://localhost:4000/v1
Add this to config.yaml in the same folder, then restart Hermes:
model:
default: gpt-6.1-sol
provider: openai-api
base_url: http://localhost:4000/v1
api_mode: codex_responses
context_length: 828400
supports_vision: true
agent:
image_input_mode: native
api_max_retries: 2
auto_recovery_cycles: 1
image_gen:
provider: openai
openai:
model: gpt-image-2.6-flare
stt:
enabled: true
provider: openai
openai:
model: gpt-4o-transcribe
compression:
threshold: 0.95
auxiliary:
compression:
timeout: 900
This setup includes image generation and voice-to-text. To switch the chat
model, set model.default to a model available to your Pool.
Keep all three addresses pointed at your Codex Pooler instance. Your Pool must
also offer the image and transcription models to use those features.
Full setup & extras — images, speech-to-text, priority processing and troubleshooting.

| System | Configuration file |
|---|---|
| macOS / Linux | ~/.pi/agent/models.json |
| Windows | %USERPROFILE%\.pi\agent\models.json |
Open models.json at the path for your system and add this configuration:
{
"providers": {
"codex-pooler": {
"name": "Codex Pooler",
"baseUrl": "http://localhost:4000/v1",
"api": "openai-responses",
"apiKey": "$CODEX_POOLER_API_KEY",
"authHeader": true,
"models": [
{
"id": "gpt-6-luna",
"name": "GPT-6 Luna via Codex Pooler",
"reasoning": true,
"input": ["text", "image"],
"contextWindow": 828400,
"maxTokens": 128000,
"thinkingLevelMap": { "xhigh": "xhigh" }
},
{
"id": "gpt-6.1-sol",
"name": "GPT-6.1 Sol via Codex Pooler",
"reasoning": true,
"input": ["text", "image"],
"contextWindow": 828400,
"maxTokens": 128000,
"thinkingLevelMap": { "xhigh": "xhigh" }
},
{
"id": "gpt-6-astra",
"name": "GPT-6 Astra via Codex Pooler",
"reasoning": true,
"input": ["text", "image"],
"contextWindow": 828400,
"maxTokens": 128000,
"thinkingLevelMap": { "xhigh": "xhigh" }
}
]
}
}
}
Add these defaults to settings.json in the same folder:
{
"defaultProvider": "codex-pooler",
"defaultModel": "gpt-6.1-sol",
"enabledModels": [
"codex-pooler/gpt-6-luna",
"codex-pooler/gpt-6.1-sol",
"codex-pooler/gpt-6-astra"
],
"compaction": { "reserveTokens": 128000 }
}
Then start Pi:
pi
Full setup & extras — installation, default models and extra options.

| System | Configuration file |
|---|---|
| macOS / Linux | ~/.omp/agent/models.yml |
| Windows | %USERPROFILE%\.omp\agent\models.yml |
Open models.yml at the path for your system and add this configuration:
providers:
codex-pooler:
baseUrl: http://localhost:4000/v1
api: openai-responses
apiKey: CODEX_POOLER_API_KEY
authHeader: true
remoteCompaction:
enabled: true
api: openai-codex-responses
endpoint: http://localhost:4000/backend-api/codex/responses/compact
v2StreamingEnabled: true
v2Endpoint: http://localhost:4000/backend-api/codex/responses
models:
- id: gpt-6-luna
name: GPT-6 Luna via Codex Pooler
reasoning: true
input: [text, image]
compat:
streamIdleTimeoutMs: 300000
contextWindow: 828400
maxTokens: 128000
- id: gpt-6.1-sol
name: GPT-6.1 Sol via Codex Pooler
reasoning: true
input: [text, image]
compat:
streamIdleTimeoutMs: 300000
contextWindow: 828400
maxTokens: 128000
- id: gpt-6-astra
name: GPT-6 Astra via Codex Pooler
reasoning: true
input: [text, image]
compat:
streamIdleTimeoutMs: 300000
contextWindow: 828400
maxTokens: 128000
Add these defaults to config.yml in the same folder:
startup:
setupWizard: fa
Codex Pooler MCP Fragen
Was ist Codex Pooler?
Es ist ein selbst gehostetes Gateway zum Ausführen von Codex-kompatiblen Agents, Tools und Automatisierungen über stabile Pool API-Keys.
Speichert Codex Pooler meine Gesprächsinhalte?
Nein, es ermöglicht dir, die Nutzung zu tracken und Anfragen zu troubleshootn, ohne Prompts, Antworten, Dateien, Bilder oder Audio zu speichern.
Wie kann ich Codex Pooler deployen?
Du kannst mit Docker Compose starten oder auf Kubernetes deployen, wenn dein Bedarf wächst.
Kann ich meine bestehenden OpenAI-kompatiblen SDKs damit nutzen?
Ja, es funktioniert mit Apps, die mit OpenAI-kompatiblen SDKs gebaut wurden, und stellt eine Base URL dafür bereit.