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Plane Agent

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Plane Agent — Model Context Protocol server

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Plane Agent — Model Context Protocol server

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CLI or API | MCP | Agent

PyPI - Version MCP Server PyPI - Downloads GitHub Repo stars GitHub forks GitHub contributors PyPI - License GitHub GitHub last commit (by committer) GitHub pull requests GitHub closed pull requests GitHub issues GitHub top language GitHub language count GitHub repo size GitHub repo file count (file type) PyPI - Wheel PyPI - Implementation

Version: 2.1.0

Documentation — Installation, deployment, usage across the API, CLI, and MCP interfaces, and guidance for provisioning a self-hosted Plane instance are maintained in the official documentation.


Table of Contents


Overview

Plane Agent is a production-grade Agent and Model Context Protocol (MCP) server designed to interface directly with Plane MCP Agent.


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.

CLI or API

This agent wraps the Plane MCP Agent 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.


MCP

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

Available MCP Tools

This table is auto-generated from the live server — do not edit by hand.

Condensed action-routed tools (MCP_TOOL_MODE=condensed)

MCP Tool Toggle Env Var Description
plane_cycles CYCLESTOOL Manage plane cycles operations.
plane_epics EPICSTOOL Manage plane epics operations.
plane_ingest KGTOOL Natively ingest Plane records into epistemic-graph as typed OWL nodes.
plane_initiatives INITIATIVESTOOL Manage plane initiatives operations.
plane_intake INTAKETOOL Manage plane intake operations.
plane_labels LABELSTOOL Manage plane labels operations.
plane_milestones MILESTONESTOOL Manage plane milestones operations.
plane_modules MODULESTOOL Manage plane modules operations.
plane_pages PAGESTOOL Manage plane pages operations.
plane_projects PROJECTSTOOL Manage plane projects operations.
plane_states STATESTOOL Manage plane states operations.
plane_users USERSTOOL Manage plane users operations.
plane_work_items WORK_ITEMSTOOL Manage plane work items operations.
plane_workspaces WORKSPACESTOOL Manage plane workspaces operations.

Verbose 1:1 API-mapped tools (MCP_TOOL_MODE=verbose or both)

102 per-operation tools — one per public API method (click to expand)
MCP Tool Toggle Env Var Description
plane_add_work_items_to_cycle APITOOL Add work items to a cycle.
plane_add_work_items_to_milestone APITOOL Add work items to a milestone.
plane_add_work_items_to_module APITOOL Add work items to a module.
plane_advanced_search_work_items APITOOL Advanced search for work items.
plane_archive_module APITOOL Archive a module.
plane_create_cycle APITOOL Create a new cycle.
plane_create_epic APITOOL Create a new epic (technically a work item with epic type).
plane_create_initiative APITOOL Create a new initiative in the workspace.
plane_create_intake_work_item APITOOL Create a new intake work item in a project.
plane_create_label APITOOL Create a new label.
plane_create_milestone APITOOL Create a new milestone.
plane_create_module APITOOL Create a new module.
plane_create_project_page APITOOL Create a new project page.
plane_create_state APITOOL Create a new state.
plane_create_work_item APITOOL Create a new work item.
plane_create_work_item_comment APITOOL Create a comment for a work item.
plane_create_work_item_link APITOOL Create a link for a work item.
plane_create_work_item_property APITOOL Create a new work item property.
plane_create_work_item_relation APITOOL Create relations for a work item.
plane_create_work_item_type APITOOL Create a new work item type.
plane_create_work_log APITOOL Create a work log for a work item.
plane_delete_cycle APITOOL Delete a cycle by ID.
plane_delete_epic APITOOL Delete an epic by ID.
plane_delete_initiative APITOOL Delete an initiative by ID.
plane_delete_intake_work_item APITOOL Delete an intake work item by work item ID.
plane_delete_milestone APITOOL Delete a milestone by ID.
plane_delete_module APITOOL Delete a module by ID.
plane_delete_project APITOOL Delete a project by ID.
plane_delete_state APITOOL Delete a state by ID.
plane_delete_work_item APITOOL Delete a work item by ID.
plane_delete_work_item_comment APITOOL Delete a comment for a work item.
plane_delete_work_item_link APITOOL Delete a link for a work item.
plane_delete_work_item_property APITOOL Delete a work item property by ID.
plane_delete_work_item_type APITOOL Delete a work item type by ID.
plane_delete_work_log APITOOL Delete a work log for a work item.
plane_get_me APITOOL Get current user information.
plane_get_project_features APITOOL Get features of a project.
plane_get_project_members APITOOL Get all members of a project.
plane_get_project_worklog_summary APITOOL Get work log summary for a project.
plane_get_workspace APITOOL Get current workspace details.
plane_get_workspace_features APITOOL Get features of the current workspace.
plane_get_workspace_members APITOOL Get all members of the current workspace.
plane_list_archived_cycles APITOOL List archived cycles in a project.
plane_list_archived_modules APITOOL List archived modules in a project.
plane_list_cycle_work_items APITOOL List work items in a cycle.
plane_list_cycles APITOOL List all cycles in a project.
plane_list_epics APITOOL List all epics in a project.
plane_list_initiatives APITOOL List all initiatives in the workspace.
plane_list_intake_work_items APITOOL List all intake work items in a project.
plane_list_labels APITOOL List all labels in a project.
plane_list_milestone_work_items APITOOL List work items in a milestone.
plane_list_milestones APITOOL List all milestones in a project.
plane_list_module_work_items APITOOL List work items in a module.
plane_list_modules APITOOL List all modules in a project.
plane_list_projects APITOOL List all projects in the workspace.
plane_list_states APITOOL List all states in a project.
plane_list_users APITOOL List all users in the workspace.
plane_list_work_item_activities APITOOL List activities for a work item.
plane_list_work_item_comments APITOOL List comments for a work item.
plane_list_work_item_links APITOOL List links for a work item.
plane_list_work_item_properties APITOOL List work item properties for a work item type.
plane_list_work_item_relations APITOOL List relations for a work item.
plane_list_work_item_types APITOOL List work item types in a project.
plane_list_work_items APITOOL List work items in a project.
plane_list_work_logs APITOOL List work logs for a work item.
plane_remove_work_item_from_cycle APITOOL Remove a work item from a cycle.
plane_remove_work_item_from_module APITOOL Remove a work item from a module.
plane_remove_work_item_relation APITOOL Remove a relation from a work item.
plane_remove_work_items_from_milestone APITOOL Remove work items from a milestone.
plane_retrieve_cycle APITOOL Retrieve a cycle by ID.
plane_retrieve_epic APITOOL Retrieve an epic by ID.
plane_retrieve_initiative APITOOL Retrieve an initiative by ID.
plane_retrieve_intake_work_item APITOOL Retrieve an intake work item by work item ID.
plane_retrieve_milestone APITOOL Retrieve a milestone by ID.
plane_retrieve_module APITOOL Retrieve a module by ID.
plane_retrieve_project APITOOL Retrieve a project by ID.
plane_retrieve_project_page APITOOL Retrieve a project page by ID.
plane_retrieve_state APITOOL Retrieve a state by ID.
plane_retrieve_work_item APITOOL Retrieve a work item by ID.
plane_retrieve_work_item_activity APITOOL Retrieve a specific activity for a work item.
plane_retrieve_work_item_by_identifier APITOOL Retrieve a work item by project identifier and issue sequence number.
plane_retrieve_work_item_comment APITOOL Retrieve a specific comment for a work item.
plane_retrieve_work_item_link APITOOL Retrieve a specific link for a work item.
plane_retrieve_work_item_property APITOOL Retrieve a work item property by ID.
plane_search_work_items APITOOL Search work items across a workspace.
plane_transfer_cycle_work_items APITOOL Transfer work items from one cycle to another.
plane_unarchive_module APITOOL Unarchive a module.
plane_update_cycle APITOOL Update a cycle by ID.
plane_update_epic APITOOL Update an epic by ID.
plane_update_initiative APITOOL Update an initiative by ID.
plane_update_intake_work_item APITOOL Update an intake work item by work item ID.
plane_update_milestone APITOOL Update a milestone by ID.
plane_update_module APITOOL Update a module by ID.
plane_update_project_features APITOOL Update features of a project.
plane_update_state APITOOL Update a state by ID.
plane_update_work_item APITOOL Update a work item by ID.
plane_update_work_item_comment APITOOL Update a comment for a work item.
plane_update_work_item_link APITOOL Update a link for a work item.
plane_update_work_item_property APITOOL Update a work item property by ID.
plane_update_work_item_type APITOOL Update a work item type by ID.
plane_update_work_log APITOOL Update a work log for a work item.
plane_update_workspace_features APITOOL Update features of the current workspace.

14 action-routed tool(s) · 102 verbose 1:1 tool(s). Each is enabled unless its <DOMAIN>TOOL toggle is set false; MCP_TOOL_MODE selects the surface (intent default — the six verb-tools, granular set loaded on demand · condensed action-routed · verbose 1:1 · both). Auto-generated — do not edit.

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


MCP Configuration Examples

Install the connector-focused [mcp] extra. Examples use plane-agent[mcp] to add FastMCP / FastAPI through agent-utilities[mcp]; the required Agent Utilities core still carries epistemic-graph[full]. The [agent-runtime] extra additionally enables model orchestration.

stdio Transport (local IDEs — Cursor, Claude Desktop, VS Code)

{
  "mcpServers": {
    "plane-mcp": {
      "command": "uvx",
      "args": [
        "--from",
        "plane-agent[mcp]",
        "plane-mcp"
      ],
      "env": {
        "MCP_TOOL_MODE": "intent",
        "CYCLESTOOL": "True",
        "EPICSTOOL": "True",
        "INITIATIVESTOOL": "True",
        "INTAKETOOL": "True",
        "KGTOOL": "True",
        "LABELSTOOL": "True",
        "MILESTONESTOOL": "True",
        "MODULESTOOL": "True",
        "PAGESTOOL": "True",
        "PLANE_API_KEY": "your_plane_api_key_here",
        "PLANE_BASE_URL": "https://api.plane.so",
        "PLANE_KG_INGEST": "true",
        "PLANE_TLS_PROFILE": "system",
        "PROJECTSTOOL": "True",
        "STATESTOOL": "True",
        "USERSTOOL": "True",
        "WORKSPACESTOOL": "True",
        "WORK_ITEMSTOOL": "True"
      }
    }
  }
}

Runtime references require an alias-aware launcher such as GraphOS. Other launchers must omit those entries and inject the resolved values through their own runtime secret boundary.

Streamable-HTTP Transport (networked / production)

{
  "mcpServers": {
    "plane-mcp": {
      "command": "uvx",
      "args": [
        "--from",
        "plane-agent[mcp]",
        "plane-mcp",
        "--transport",
        "streamable-http",
        "--port",
        "8000"
      ],
      "env": {
        "TRANSPORT": "streamable-http",
        "HOST": "127.0.0.1",
        "PORT": "8000",
        "MCP_TOOL_MODE": "intent",
        "CYCLESTOOL": "True",
        "EPICSTOOL": "True",
        "INITIATIVESTOOL": "True",
        "INTAKETOOL": "True",
        "KGTOOL": "True",
        "LABELSTOOL": "True",
        "MILESTONESTOOL": "True",
        "MODULESTOOL": "True",
        "PAGESTOOL": "True",
        "PLANE_API_KEY": "your_plane_api_key_here",
        "PLANE_BASE_URL": "https://api.plane.so",
        "PLANE_KG_INGEST": "true",
        "PLANE_TLS_PROFILE": "system",
        "PROJECTSTOOL": "True",
        "STATESTOOL": "True",
        "USERSTOOL": "True",
        "WORKSPACESTOOL": "True",
        "WORK_ITEMSTOOL": "True"
      }
    }
  }
}

Alternatively, connect to a pre-deployed Streamable-HTTP instance by url:

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

Run a reviewed container image as a least-privilege stdio child (no listener or published port):

docker run -i --rm \
  --read-only \
  --cap-drop=ALL \
  --security-opt=no-new-privileges \
  --pids-limit=256 \
  --tmpfs /tmp:rw,noexec,nosuid,nodev,size=64m \
  -e TRANSPORT=stdio \
  -e MCP_TOOL_MODE=intent \
  -e CYCLESTOOL=True \
  -e EPICSTOOL=True \
  -e INITIATIVESTOOL=True \
  -e INTAKETOOL=True \
  -e KGTOOL=True \
  -e LABELSTOOL=True \
  -e MILESTONESTOOL=True \
  -e MODULESTOOL=True \
  -e PAGESTOOL=True \
  -e PLANE_API_KEY=your_plane_api_key_here \
  -e PLANE_BASE_URL=https://api.plane.so \
  -e PLANE_KG_INGEST=true \
  -e PLANE_TLS_PROFILE=system \
  -e PROJECTSTOOL=True \
  -e STATESTOOL=True \
  -e USERSTOOL=True \
  -e WORKSPACESTOOL=True \
  -e WORK_ITEMSTOOL=True \
  registry.example.invalid/plane-agent@sha256:<digest> plane-mcp

For containerized network HTTP, supply an authenticated TLS ingress (or direct server TLS), exact MCP_ALLOWED_HOSTS, and an exact trusted-proxy CIDR policy through the operator-owned deployment profile. The generator does not emit an unauthenticated non-loopback listener.

Auto-generated from the code-read env surface (MCP_TOOL_MODE + package vars) — do not edit.

Additional Deployment Options

plane-agent can run as a local stdio process or container, or behind a remote network boundary. The Deployment guide carries the detailed transport contract.

  • Local container — launch a reviewed immutable image as a least-privilege stdio child with no listener or published port.
  • Remote URL — connect through an operator-supplied authenticated HTTPS ingress. Keep its URL, outbound identity references, trust profile, and exact MCP_ALLOWED_HOSTS in AgentConfig.

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 PLANE_BASE_URL="your_value"
export PLANE_WORKSPACE_SLUG="your_value"
export DEBUG="your_value"
export PYTHONUNBUFFERED="your_value"
export PLANE_API_KEY="your_value"

# Run the agent server
plane-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:
  plane-agent-mcp:
    image: example/plane-agent:mcp
    container_name: plane-agent-mcp
    hostname: plane-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"

  plane-agent-agent:
    image: example/plane-agent@sha256:<digest>
    container_name: plane-agent-agent
    hostname: plane-agent-agent
    restart: always
    depends_on:
      - plane-agent-mcp
    env_file:
      - ../.env
    command: [ "plane-agent" ]
    environment:
      - PYTHONUNBUFFERED=1
      - HOST=0.0.0.0
      - PORT=9004
      - MCP_URL=http://plane-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/overview.md and docs/index.md.


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

Environment Variables

Package environment variables

Variable Example Description
HOST 0.0.0.0
PORT 8000
TRANSPORT stdio options: stdio, streamable-http, sse
ENABLE_OTEL True
OTEL_EXPORTER_OTLP_ENDPOINT http://localhost:8080/api/public/otel
OTEL_EXPORTER_OTLP_PUBLIC_KEY secret-injected
OTEL_EXPORTER_OTLP_SECRET_KEY secret-injected
OTEL_EXPORTER_OTLP_PROTOCOL http/protobuf
EUNOMIA_TYPE none options: none, embedded, remote
EUNOMIA_POLICY_FILE mcp_policies.json
EUNOMIA_REMOTE_URL http://eunomia-server:8000
PLANE_BASE_URL https://api.plane.so
PLANE_WORKSPACE_SLUG
PLANE_TLS_PROFILE system Named outbound TLS policy from AgentConfig. Use a reference for runtime-only trust material; peer and hostname verification remain mandatory.
PLANE_TLS_PROFILE_REF
PLANE_KG_INGEST true
DEBUG False
PYTHONUNBUFFERED 1
PLANE_API_KEY secret-injected
PROJECTSTOOL True
WORK_ITEMSTOOL True
CYCLESTOOL True
EPICSTOOL True
MILESTONESTOOL True
MODULESTOOL True
STATESTOOL True
USERSTOOL True
WORKSPACESTOOL True
INITIATIVESTOOL True
INTAKETOOL True
LABELSTOOL True
PAGESTOOL True
KGTOOL True

Inherited agent-utilities variables (apply to every connector)

Variable Example Description
MCP_TOOL_MODE intent Tool surface: intent | condensed | verbose | both
MCP_ENABLED_TOOLS Comma-separated tool allow-list
MCP_DISABLED_TOOLS Comma-separated tool deny-list
MCP_ENABLED_TAGS Comma-separated tag allow-list
MCP_DISABLED_TAGS Comma-separated tag deny-list
MCP_CLIENT_AUTH Outbound MCP child auth: oidc-client-credentials | basic | none
OIDC_CLIENT_ID OIDC client id (service-account auth)
OIDC_CLIENT_SECRET_REF secret://identity/oidc-client-secret Runtime secret reference for the OIDC service account
MCP_BASIC_AUTH_USERNAME HTTP Basic username (MCP_CLIENT_AUTH=basic)
MCP_BASIC_AUTH_PASSWORD_REF secret://identity/mcp-basic-password Runtime secret reference for HTTP Basic auth (MCP_CLIENT_AUTH=basic)
MCP_URL http://localhost:8000/mcp URL of the MCP server the agent connects to
PROVIDER openai LLM provider for the agent
MODEL_ID gpt-4o Model id for the agent
ENABLE_WEB_UI True Serve the AG-UI web interface

33 package + 14 inherited variable(s). Auto-generated from .env.example + the shared agent-utilities set — do not edit.

The Plane Agent supports the following environment variables for configuration and integration:

Variable Description
PLANE_BASE_URL The base URL of the Plane instance.
PLANE_WORKSPACE_SLUG The workspace slug of the Plane workspace.
PLANE_API_KEY The API key for authentication with Plane.
MCP_URL The URL of the MCP server.
MODEL_ID Default LLM model identifier (e.g. gpt-4o).
PROVIDER The LLM provider (e.g. openai, anthropic).
ENABLE_WEB_UI Set to True to enable the built-in Web UI.
ENABLE_OTEL Set to True to enable OpenTelemetry telemetry.
AGENT_UTILITIES_TESTING Set to True during testing to bypass production setups.
AUTH_TYPE The authentication type to use (e.g., jwt, none).
DEFAULT_API_KEY Default API key for fast server fallback authentication.
OTEL_EXPORTER_OTLP_ENDPOINT The OpenTelemetry OTLP endpoint.
PROJECTSTOOL Set to True/False to toggle the Projects tool module.
WORK_ITEMSTOOL Set to True/False to toggle the Work Items tool module.
CYCLESTOOL Set to True/False to toggle the Cycles tool module.
EPICSTOOL Set to True/False to toggle the Epics tool module.
MILESTONESTOOL Set to True/False to toggle the Milestones tool module.
MODULESTOOL Set to True/False to toggle the Modules tool module.
STATESTOOL Set to True/False to toggle the States tool module.
USERSTOOL Set to True/False to toggle the Users tool module.
WORKSPACESTOOL Set to True/False to toggle the Workspaces tool module.
INITIATIVESTOOL Set to True/False to toggle the Initiatives tool module.
INTAKETOOL Set to True/False to toggle the Intake tool module.
LABELSTOOL Set to True/False to toggle the Labels tool module.
PAGESTOOL Set to True/False to toggle the Pages tool module.

Installation

Pick the extra that matches what you want to run:

Extra Installs Use when
plane-agent[mcp] Connector-focused MCP server (agent-utilities[mcp] — FastMCP/FastAPI + epistemic-graph[full]) You only run the MCP server (smallest install / image)
plane-agent[agent] Agent runtime (agent-utilities[agent-runtime,logfire] — model orchestration + epistemic-graph[full]) You run the integrated agent
plane-agent[all] Everything (mcp + agent + logfire) Development / both surfaces
# Connector-focused MCP server (includes the shared graph engine)
uv pip install "plane-agent[mcp]"

# Agent runtime (adds model orchestration to the shared graph engine)
uv pip install "plane-agent[agent]"

# Everything (development)
uv pip install "plane-agent[all]"      # or: python -m pip install "plane-agent[all]"

Container images (:mcp vs :agent)

One multi-stage docker/Dockerfile builds two right-sized images, selected by --target:

Image tag Build target Contents Entrypoint
example/plane-agent:mcp --target mcp plane-agent[mcp]connector-focused, includes epistemic-graph[full]; no model-orchestration stack plane-mcp
example/plane-agent@sha256:<digest> --target agent (default) plane-agent[agent]agent runtime, model orchestration + epistemic-graph[full] plane-agent
docker build --target mcp   -t example/plane-agent:mcp    docker/   # connector-focused MCP server
docker build --target agent -t example/plane-agent:agent-local docker/   # agent runtime

docker/mcp.compose.yml runs the connector-focused :mcp server; docker/agent.compose.yml runs the agent (immutable agent digest) with a co-located :mcp sidecar.

Knowledge-graph database (epistemic-graph)

Both [mcp] and [agent] carry the epistemic-graph engine through the required Agent Utilities core dependency (epistemic-graph[full]). The [mcp] extra keeps the server connector-focused; [agent] additionally enables model orchestration. Local deployments can use the bundled engine. For production or shared state, run epistemic-graph as a dedicated database service and configure the runtime to use it. Deployment recipes (single-node + Raft HA), connection configuration, and architecture diagrams are documented in the epistemic-graph deployment guide.


Documentation

The complete documentation is published as the official documentation site and is the recommended reference for installation, deployment, and day-to-day operation.

Page Contents
Installation pip, source, uv, prebuilt Docker image
Deployment run the MCP server and agent, Compose, Caddy + Technitium, env config
Usage the MCP tools, the Api client, the CLI
Backing Platform deploy a self-hosted Plane instance with Docker
Overview ecosystem role, enterprise posture, architecture
Concepts concept registry (CONCEPT:PLANE-*)

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

Deploy with agent-utilities-deployment

Provision this package with the consolidated agent-utilities-deployment workflow. It selects an installed-package, editable-source, or immutable-container path; records only runtime secret and TLS-profile references in AgentConfig; and runs doctor, registration, policy, observability, and rollback gates. Ask your agent to "deploy plane-agent with agent-utilities-deployment".

Install mode Command
Installed package uv tool install "plane-agent[mcp]", then run plane-mcp
Editable source uv pip install -e ".[agent]", then run plane-mcp
Immutable container deploy registry.example.invalid/plane-agent@sha256:<digest> through the operator-selected orchestrator

The repository embeds no deployment profile, credential value, certificate path, or environment-specific endpoint. Supply those at runtime through AgentConfig and the configured secret provider.

Governed capability contract

This package ships a compact canonical skill surface with specialist procedures kept as referenced workflows. The current MCP tools, skill metadata, connector_manifest.yml, ontology, mappings, shapes, fixtures, migrations, tool-schema fingerprints, and certification metadata form one versioned capability contract. Validate them together; do not rely on stale tool names or historical per-task skill wrappers.

Runtime endpoints, credentials, certificate trust, tenant identity, retention, and observability policy are deployment inputs and are never packaged values. See Configuration, trust, and privacy before enabling a network transport, connector ingestion, GraphOS delegation, or trace export.

from github.com/Knuckles-Team/plane-agent

Установка Plane Agent

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/Knuckles-Team/plane-agent

FAQ

Plane Agent MCP бесплатный?

Да, Plane Agent MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Plane Agent?

Нет, Plane Agent работает без API-ключей и переменных окружения.

Plane Agent — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Plane Agent в Claude Desktop, Claude Code или Cursor?

Открой Plane Agent на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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