Postiz Agent

CLI or API | MCP | Agent

Version: 0.18.0

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Overview

Postiz Agent is a production-grade Agent and Model Context Protocol (MCP) server designed to interface directly with Agent for interacting with Postiz Public API.

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Key Features

• Consolidated Action-Routed MCP Tools: Minimizes token overhead and eliminates tool bloat in LLM contexts by grouping methods into optimized, togglable tool modules.
• Enterprise-Grade Security: Comprehensive support for Eunomia policies, OIDC token delegation, and granular execution context tracking.
• Integrated Graph Agent: Built-in Pydantic AI agent supporting the Agent Control Protocol (ACP) and standard Web interfaces (AG-UI).
• Native Telemetry & Tracing: Out-of-the-box OpenTelemetry exports and native Langfuse tracing.

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CLI or API

This agent wraps the Agent for interacting with Postiz Public API API. You can interact with it programmatically or via its integrated execution entrypoints.

Detailed instructions on how to use the underlying API wrappers, extended schema bindings, and developer SDK references are maintained in docs/index.md.

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MCP

This server utilizes dynamic Action-Routed tools to optimize token overhead and maximize IDE compatibility.

Available MCP Tools

Tool Module	Toggle Env Var	Enabled by Default	Description & Nested Methods
Integrations	INTEGRATIONS_TOOL	True	Manage postiz integrations operations. Action-routed methods: postiz_check_connection, postiz_delete_channel, postiz_find_slot, postiz_get_integration_url, postiz_list_integrations.
Posts	POSTS_TOOL	True	Manage postiz posts operations. Action-routed methods: postiz_create_post, postiz_delete_post, postiz_delete_post_by_group, postiz_get_missing_content, postiz_list_posts, postiz_update_release_id.
Uploads	UPLOADS_TOOL	True	Manage postiz uploads operations. Action-routed methods: postiz_upload_file, postiz_upload_from_url.
Analytics	ANALYTICS_TOOL	True	Manage postiz analytics operations. Action-routed methods: postiz_get_analytics, postiz_get_post_analytics.
Notifications	NOTIFICATIONS_TOOL	True	Manage postiz notifications operations. Action-routed methods: postiz_list_notifications.
Video	VIDEO_TOOL	True	Manage postiz video operations. Action-routed methods: postiz_generate_video, postiz_video_function.

Detailed tool schemas, parameter shapes, and validation constraints are preserved in docs/mcp.md.

Dynamic Tool Selection & Visibility

This MCP server supports dynamic toolset selection and visibility filtering at runtime. This allows you to restrict the set of exposed tools in order to prevent blowing up the LLM's context window.

You can configure tool filtering via multiple input channels:

• CLI Arguments: Pass --tools or --toolsets (or their disabled counterparts --disabled-tools and --disabled-toolsets) during startup.
• Environment Variables: Define standard environment variables:
  • MCP_ENABLED_TOOLS / MCP_DISABLED_TOOLS
  • MCP_ENABLED_TAGS / MCP_DISABLED_TAGS
• HTTP SSE Request Headers: Pass custom headers during transport initialization:
  • x-mcp-enabled-tools / x-mcp-disabled-tools
  • x-mcp-enabled-tags / x-mcp-disabled-tags
• HTTP SSE Request Query Parameters: Append query parameters directly to your transport connection URL:
  • ?tools=tool1,tool2
  • ?tags=tag1

When query strings or parameters are supplied, an LLM-free Knowledge Graph resolution layer (using DynamicToolOrchestrator) matches query intents against known tool tags, names, or descriptions, with safe fallback and automated 24-hour background cache refreshing.

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MCP Configuration Examples

stdio Transport (Recommended for local IDEs e.g., Cursor, Claude Desktop)

Configure your IDE's mcp.json to launch the MCP server via uvx:

{
  "mcpServers": {
    "postiz-agent": {
      "command": "uvx",
      "args": [
        "--from",
        "postiz-agent",
        "postiz-mcp"
      ],
      "env": {
        "POSTIZ_SUBDOMAIN": "your_postiz_subdomain_here",
        "POSTIZ_TOKEN": "your_postiz_token_here"
      }
    }
  }
}

Streamable-HTTP Transport (Recommended for production deployments)

Configure your client's mcp.json to launch the Streamable-HTTP server via uvx with explicit host and port definition:

{
  "mcpServers": {
    "postiz-agent": {
      "command": "uvx",
      "args": [
        "--from",
        "postiz-agent",
        "postiz-mcp"
      ],
      "env": {
        "TRANSPORT": "streamable-http",
        "HOST": "0.0.0.0",
        "PORT": "8000",
        "POSTIZ_SUBDOMAIN": "your_postiz_subdomain_here",
        "POSTIZ_TOKEN": "your_postiz_token_here"
      }
    }
  }
}

Alternatively, connect to a pre-deployed remote or local Streamable-HTTP instance:

{
  "mcpServers": {
    "postiz-agent": {
      "url": "http://localhost:8000/postiz-agent/mcp"
    }
  }
}

Deploying the Streamable-HTTP server via Docker:

docker run -d \
  --name postiz-agent-mcp \
  -p 8000:8000 \
  -e TRANSPORT=streamable-http \
  -e PORT=8000 \
  -e POSTIZ_SUBDOMAIN="your_value" \
  -e POSTIZ_TOKEN="your_value" \
  knucklessg1/postiz-agent:latest

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Agent

This repository features a fully integrated Pydantic AI Graph Agent. It communicates over the Agent Control Protocol (ACP) and interacts seamlessly with the Agent Web UI (AG-UI) and Terminal interface.

Running the Agent CLI

To start the interactive command-line agent:

# Set credentials
export POSTIZ_SUBDOMAIN="your_value"
export POSTIZ_TOKEN="your_value"

# Run the agent server
postiz-agent --provider openai --model-id gpt-4o

Docker Compose Orchestration

The following docker/agent.compose.yml configures the Agent, Web UI, and Terminal Interface together:

version: '3.8'

services:
  postiz-agent-mcp:
    image: knucklessg1/postiz-agent:latest
    container_name: postiz-agent-mcp
    hostname: postiz-agent-mcp
    restart: always
    env_file:
      - ../.env
    environment:
      - PYTHONUNBUFFERED=1
      - HOST=0.0.0.0
      - PORT=8000
      - TRANSPORT=streamable-http
    ports:
      - "8000:8000"
    healthcheck:
      test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 10s
    logging:
      driver: json-file
      options:
        max-size: "10m"
        max-file: "3"

  postiz-agent-agent:
    image: knucklessg1/postiz-agent:latest
    container_name: postiz-agent-agent
    hostname: postiz-agent-agent
    restart: always
    depends_on:
      - postiz-agent-mcp
    env_file:
      - ../.env
    command: [ "postiz-agent" ]
    environment:
      - PYTHONUNBUFFERED=1
      - HOST=0.0.0.0
      - PORT=9004
      - MCP_URL=http://postiz-agent-mcp:8000/mcp
      - PROVIDER=${PROVIDER:-openai}
      - MODEL_ID=${MODEL_ID:-gpt-4o}
      - ENABLE_WEB_UI=True
      - ENABLE_OTEL=True
    ports:
      - "9004:9004"
    healthcheck:
      test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:9004/health')"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 10s
    logging:
      driver: json-file
      options:
        max-size: "10m"
        max-file: "3"

Detailed graph node architecture explanations, custom skill configurations, and agentic trace guides are available in docs/agent.md.

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Security & Governance

Built directly upon the enterprise-ready agent-utilities core, standard security parameters are fully supported:

Access Control & Policy Enforcement

• Eunomia Policies: Fine-grained, policy-driven tool authorization. Supports none, local embedded (mcp_policies.json), or centralized remote modes.
• OIDC Token Delegation: Compliant with RFC 8693 token exchange for flowing authenticating user credentials from Web UI / ACP → Agent → MCP.
• Scoped Credentials: Execution context runs restricted to the specific caller identity.

Runtime Security Grid

Feature	Functionality	Enablement
Tool Guard	Sensitivity inspection with human-in-the-loop validation	Enabled by default
Prompt Injection Defense	Input scanning, repetition monitoring, and recursive loop blocks	Enabled by default
Context Safety Guard	Stuck-loop detectors and contextual overflow preemptive alerts	Enabled by default

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Environment Variables

The agent and MCP server can be configured using the following environment variables:

Variable	Description	Default / Type
HOST	Host to bind the server to (Streamable-HTTP).	0.0.0.0
PORT	Port to bind the server to.	8000
TRANSPORT	MCP communication channel style. Options: stdio, streamable-http, sse.	stdio
DEFAULT_AGENT_NAME	Display name for the Pydantic AI Graph Agent.	"Postiz Agent"
AGENT_DESCRIPTION	System description metadata for the Pydantic AI Graph Agent.	Loaded from manifest
AGENT_SYSTEM_PROMPT	Custom prompt injected into the Pydantic AI Graph Agent core.	Loaded from manifest
POSTIZ_TOKEN	API authentication token used for Postiz endpoints.	Required
POSTIZ_URL	Base endpoint URL for the Postiz Public API.	https://api.postiz.com/public/v1
POSTIZ_SUBDOMAIN	User account subdomain registered with Postiz.	Optional
POSTIZ_AGENT_VERIFY	Whether to enforce HTTPS certificate verification.	True
AUTH_TYPE	Authentication method. Option: token.	token
ENABLE_OTEL	Whether to enable OpenTelemetry exporter logs.	True
OTEL_EXPORTER_OTLP_ENDPOINT	Enterprise telemetry collection OTLP target URL.	Optional
EUNOMIA_TYPE	Access control policy engine mode. Options: none, embedded, remote.	none
EUNOMIA_POLICY_FILE	Path to the local policy configuration file.	mcp_policies.json
INTEGRATIONSTOOL	Toggle to enable/disable the Integrations MCP tool group.	True
POSTSTOOL	Toggle to enable/disable the Posts MCP tool group.	True
UPLOADSTOOL	Toggle to enable/disable the Uploads MCP tool group.	True
ANALYTICSTOOL	Toggle to enable/disable the Analytics MCP tool group.	True
NOTIFICATIONSTOOL	Toggle to enable/disable the Notifications MCP tool group.	True
VIDEOTOOL	Toggle to enable/disable the Video MCP tool group.	True

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Installation

Install the Python package locally:

# Using uv (highly recommended)
uv pip install postiz-agent[all]

# Using standard pip
python -m pip install postiz-agent[all]

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Repository Owners

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Contribute

Contributions are welcome! Please ensure code quality by executing local checks before submitting pull requests:

• Format code using ruff format .
• Lint code using ruff check .
• Validate type-safety with mypy .
• Execute test suites using pytest