What can @heroku/mcp-server do?

heroku app lifecycle management via mcp protocol, heroku app configuration and environment variable management, heroku dyno and resource scaling via agent instructions, heroku app deployment and release management, heroku add-on provisioning and lifecycle management, heroku app monitoring and log retrieval via mcp, heroku app creation and deletion with configuration, heroku team and collaborator management

@heroku/mcp-server

MCP ServerFree

Heroku Platform MCP Server

Open Source

/ 100

8 capabilities

Capabilities8 decomposed

heroku app lifecycle management via mcp protocol

Medium confidence

Exposes Heroku Platform API operations (create, deploy, scale, restart apps) through the Model Context Protocol, allowing LLM agents and Claude to directly invoke Heroku CLI-equivalent commands without shell execution. Uses MCP's tool-calling schema to map Heroku API endpoints to structured function definitions with parameter validation and response serialization.

Solves for

I want my AI agent to deploy code to Heroku without manual interventionI need Claude to manage app scaling and resource allocation based on monitoring dataI want to automate Heroku app lifecycle tasks (create, delete, restart) through natural languageI need to integrate Heroku operations into an agentic workflow without writing custom API clients

Best for

DevOps engineers building AI-assisted deployment workflows

Solo developers automating Heroku app management through Claude

Teams integrating Heroku into LLM-powered CI/CD pipelines

Requires

Node.js 16+ (MCP server runtime)

Heroku API token (generated via `heroku auth:token` or OAuth)

MCP client implementation (Claude Desktop, custom agent framework, or compatible tool)

Limitations

Requires valid Heroku API token with appropriate OAuth scopes — no built-in token refresh or rotation

MCP protocol overhead adds ~100-200ms per request vs direct REST calls

Limited to operations exposed by Heroku Platform API v3 — advanced features like private spaces require additional configuration

What makes it unique

Implements Heroku Platform API as MCP tools with schema-based function calling, enabling LLM agents to invoke Heroku operations natively without shell commands or custom API wrappers. Uses MCP's standardized tool registry pattern to expose Heroku endpoints as first-class agent capabilities.

vs alternatives

Provides native Heroku integration for Claude and MCP-compatible agents without requiring custom REST client code or shell script execution, unlike ad-hoc Heroku CLI automation or generic HTTP tool wrappers.

heroku app configuration and environment variable management

Medium confidence

Allows reading, writing, and updating Heroku app config variables (environment variables) through MCP tool calls, with support for bulk operations and validation. Implements config var CRUD operations by wrapping Heroku's config endpoint, enabling agents to manage secrets, database URLs, and feature flags without direct API access.

Solves for

I want Claude to update database connection strings when provisioning new add-onsI need to rotate API keys and secrets across multiple Heroku apps via an agentI want to enable/disable feature flags by updating config variables through natural languageI need to retrieve current environment configuration for debugging or auditing purposes

Best for

Platform engineers managing configuration across multiple Heroku apps

DevOps teams automating secret rotation and config updates

Developers building self-service app configuration tools with AI

Requires

Heroku API token with 'read' and 'write' scopes for target apps

Valid Heroku app name or ID

MCP client with tool-calling support

Limitations

No built-in encryption for sensitive values — config vars are base64-encoded in transit but stored plaintext in Heroku

Bulk config updates are not atomic — partial failures may leave apps in inconsistent state

No change history or rollback mechanism — requires external versioning to track config changes

What makes it unique

Exposes Heroku config var operations as MCP tools with schema validation, allowing LLM agents to safely read and modify environment configuration without direct API access. Implements parameter validation to prevent invalid variable names and enforces Heroku's size constraints at the tool layer.

vs alternatives

Safer than raw Heroku CLI automation because MCP schema validation prevents malformed config updates, and integrates directly with Claude's tool-calling interface without requiring shell script parsing or error handling.

heroku dyno and resource scaling via agent instructions

Medium confidence

Enables LLM agents to scale Heroku dynos (change dyno type, adjust process counts) through MCP tool calls with parameter validation. Maps natural language scaling requests to Heroku's dyno formation API, supporting both vertical scaling (dyno type changes) and horizontal scaling (process count adjustments) with real-time status feedback.

Solves for

I want Claude to automatically scale up dynos when monitoring alerts indicate high loadI need to downscale to cheaper dyno types during off-peak hours to reduce costsI want to adjust worker process counts based on queue depth reported by an agentI need to scale multiple apps in parallel based on traffic patterns

Best for

DevOps teams automating cost optimization through dynamic scaling

Startups building self-healing infrastructure with AI agents

Teams implementing auto-scaling policies driven by monitoring data

Requires

Heroku API token with 'write' scope for dyno formation

Valid app name and process type (web, worker, etc.)

MCP client with tool-calling capability

Limitations

Scaling operations are not instantaneous — dyno restarts typically take 10-30 seconds, during which app is briefly unavailable

No built-in cost estimation — agents must reference external pricing data to make cost-aware scaling decisions

Scaling down may cause data loss if apps maintain in-memory state — no automatic persistence layer

What makes it unique

Implements dyno scaling as MCP tools with validation for dyno type compatibility and process count limits, allowing agents to make scaling decisions based on real-time metrics without manual intervention. Provides immediate feedback on scaling operation status through MCP response serialization.

vs alternatives

More reliable than shell-based Heroku CLI scaling because MCP schema validation prevents invalid dyno type requests, and integrates with Claude's reasoning to make context-aware scaling decisions based on application state.

heroku app deployment and release management

Medium confidence

Exposes Heroku deployment operations (trigger builds, manage releases, view deployment history) through MCP tools, enabling agents to deploy code and manage release rollbacks. Integrates with Heroku's build and release APIs to provide deployment status tracking and release information without requiring direct git push or CLI commands.

Solves for

I want Claude to deploy the latest code from a git branch to a Heroku appI need to rollback to a previous release if deployment health checks failI want to view deployment history and release notes for auditing purposesI need to trigger builds and monitor deployment progress through an agent

Best for

Teams automating CI/CD pipelines with AI-driven deployment decisions

DevOps engineers building intelligent rollback mechanisms

Developers implementing self-service deployment workflows

Requires

Heroku API token with 'write' scope for builds and releases

Git repository configured with Heroku remote or GitHub integration enabled

Valid app name and branch/commit reference

Limitations

Requires Heroku git remote or GitHub integration — cannot deploy arbitrary code without prior setup

Build times vary (2-10 minutes) — agents must handle async operations and polling for completion

No built-in health check integration — rollback decisions must be made by external monitoring systems

What makes it unique

Maps Heroku's build and release APIs to MCP tools with async operation tracking, allowing agents to initiate deployments and poll for completion status without blocking. Implements release history queries to enable intelligent rollback decisions based on deployment metadata.

vs alternatives

Safer than git push-based deployments because agents can validate build success and health before committing to a release, and provides native rollback capabilities without manual intervention or git history manipulation.

heroku add-on provisioning and lifecycle management

Medium confidence

Enables agents to provision, configure, and manage Heroku add-ons (databases, caching, monitoring services) through MCP tool calls. Implements add-on CRUD operations by wrapping Heroku's add-on API, supporting plan selection, attachment to apps, and deprovisioning with proper cleanup.

Solves for

I want Claude to provision a PostgreSQL database when creating a new appI need to upgrade a Redis cache plan based on memory usage metricsI want to attach monitoring add-ons to multiple apps in parallelI need to deprovision add-ons and clean up resources when shutting down apps

Best for

Platform engineers automating infrastructure provisioning

Startups building self-service app creation workflows

Teams managing add-on lifecycle at scale

Requires

Heroku API token with 'write' scope for add-ons

Valid app name

Add-on service identifier (e.g., heroku-postgresql, heroku-redis)

Limitations

Add-on provisioning is asynchronous — typically takes 30 seconds to 5 minutes, requires polling for completion

Plan upgrades may cause brief service interruptions — no zero-downtime upgrade option for most add-ons

Deprovisioning is destructive and irreversible — no built-in backup or recovery mechanism

What makes it unique

Exposes Heroku add-on lifecycle as MCP tools with async operation tracking and plan validation, allowing agents to provision infrastructure without manual Heroku dashboard interaction. Implements credential exposure through MCP responses to enable automatic configuration of provisioned services.

vs alternatives

More reliable than manual add-on provisioning because agents can validate plan compatibility and region availability before provisioning, and automatically configure apps with provisioned service credentials.

heroku app monitoring and log retrieval via mcp

Medium confidence

Provides agents with access to Heroku app logs, metrics, and status information through MCP tool calls, enabling real-time monitoring and troubleshooting without dashboard access. Implements log streaming and metric queries by wrapping Heroku's log and metrics APIs, with filtering and time-range support.

Solves for

I want Claude to retrieve recent error logs to diagnose app failuresI need to check dyno memory usage and CPU metrics to inform scaling decisionsI want to monitor app status and receive alerts when health checks failI need to retrieve logs for specific processes (web, worker) to debug issues

Best for

DevOps teams building AI-assisted troubleshooting workflows

Developers debugging production issues through natural language queries

Teams implementing intelligent alerting based on log analysis

Requires

Heroku API token with 'read' scope

Valid app name

MCP client with streaming or polling support

Limitations

Log retention is limited to 1500 lines per app — historical analysis requires external log aggregation

Metrics API has 1-minute granularity — fine-grained performance analysis requires external monitoring tools

Log streaming is not real-time through MCP — agents see batched logs with potential 30-60 second delay

What makes it unique

Integrates Heroku's log and metrics APIs as MCP tools with time-range filtering and process-type selection, enabling agents to retrieve and analyze app telemetry without external monitoring tools. Implements log retrieval with structured output for agent-friendly parsing.

vs alternatives

More accessible than Heroku dashboard monitoring because agents can query logs and metrics programmatically and correlate data across multiple queries, enabling intelligent troubleshooting without manual log review.

heroku app creation and deletion with configuration

Medium confidence

Enables agents to create new Heroku apps with initial configuration (buildpack, region, stack) and delete apps through MCP tool calls. Implements app lifecycle operations by wrapping Heroku's app creation and deletion APIs, with support for specifying app name, region, and buildpack preferences.

Solves for

I want Claude to create a new Heroku app with a specific buildpack and regionI need to provision multiple apps in parallel for testing or staging environmentsI want to clean up old apps and free up resources when they're no longer neededI need to create apps with specific configurations (stack version, region) based on requirements

Best for

Platform teams automating app provisioning workflows

Startups building self-service app creation for users

DevOps engineers managing multi-app deployments

Requires

Heroku API token with 'write' scope for app creation/deletion

Unique app name (or auto-generation strategy)

Valid region identifier (us, eu, etc.)

Limitations

App creation is asynchronous — typically takes 5-10 seconds, requires polling for completion

App names must be globally unique across Heroku — agents must handle naming conflicts and retry logic

Deletion is irreversible — no built-in backup or recovery mechanism for deleted apps

What makes it unique

Exposes Heroku app creation and deletion as MCP tools with async operation tracking and naming conflict resolution, allowing agents to provision infrastructure without manual dashboard interaction. Implements region and buildpack validation to prevent invalid app configurations.

vs alternatives

More reliable than manual app creation because agents can validate region and buildpack compatibility before provisioning, and automatically handle naming conflicts through retry logic or name generation strategies.

heroku team and collaborator management

Medium confidence

Allows agents to manage team membership and collaborator access to Heroku apps through MCP tool calls, supporting role-based access control (owner, collaborator, member). Implements team operations by wrapping Heroku's team and app collaborator APIs, enabling agents to grant/revoke access and manage team structure.

Solves for

I want Claude to grant a developer access to a specific app with collaborator roleI need to revoke access for team members who are leaving the organizationI want to manage team membership and assign roles based on responsibilitiesI need to audit who has access to critical apps and update permissions

Best for

Platform teams managing access control at scale

Organizations implementing least-privilege access policies

DevOps teams automating onboarding/offboarding workflows

Requires

Heroku API token with 'write' scope for team and collaborator management

Valid app name or team identifier

Email address of user to grant/revoke access

Limitations

Role-based access control is limited to owner, collaborator, and member — no fine-grained permission scoping

Access changes are immediate — no approval workflow or staged rollout mechanism

No built-in audit logging — access changes must be tracked externally

What makes it unique

Exposes Heroku team and collaborator APIs as MCP tools with role validation, enabling agents to manage access control without manual Heroku dashboard interaction. Implements permission checks to prevent invalid role assignments.

vs alternatives

More auditable than manual access management because agents can log all access changes and enforce consistent role assignment policies, reducing human error in permission management.

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

Related Artifactssharing capabilities

Artifacts that share capabilities with @heroku/mcp-server, ranked by overlap. Discovered automatically through the match graph.

MCP Server33

@heroku/mcp-server

Heroku Platform MCP Server

dyno management and configuration via mcp toolsheroku app lifecycle management via mcp protocolenvironment variable and config management via mcpmulti-app batch operations via mcp tool composition

4 shared capabilities

Agent28

Monoid

Empowering Large Language Models with Real-time AI Agent...

agent deployment and scaling

1 shared capability

MCP Server40

mcp-agent

Build effective agents using Model Context Protocol and simple workflow patterns

declarative configuration system with environment variable binding

1 shared capability

MCP Server24

Kubernetes

** - Connect to Kubernetes cluster and manage pods, deployments, services.

deployment and configuration management across environments

1 shared capability

MCP Server40

network-ai

AI agent orchestration framework for TypeScript/Node.js - 27 adapters (LangChain, AutoGen, CrewAI, OpenAI Assistants, LlamaIndex, Semantic Kernel, Haystack, DSPy, Agno, MCP, OpenClaw, A2A, Codex, MiniMax, NemoClaw, APS, Copilot, LangGraph, Anthropic Compu

agent configuration management and deployment

1 shared capability

MCP Server44

mcp-use

The fullstack MCP framework to develop MCP Apps for ChatGPT / Claude & MCP Servers for AI Agents.

configuration management and environment-based deployment

1 shared capability

Best For

✓DevOps engineers building AI-assisted deployment workflows
✓Solo developers automating Heroku app management through Claude
✓Teams integrating Heroku into LLM-powered CI/CD pipelines
✓Founders prototyping serverless app management with AI agents
✓Platform engineers managing configuration across multiple Heroku apps
✓DevOps teams automating secret rotation and config updates
✓Developers building self-service app configuration tools with AI
✓Teams needing audit trails of config changes via LLM-driven workflows

Known Limitations

⚠Requires valid Heroku API token with appropriate OAuth scopes — no built-in token refresh or rotation
⚠MCP protocol overhead adds ~100-200ms per request vs direct REST calls
⚠Limited to operations exposed by Heroku Platform API v3 — advanced features like private spaces require additional configuration
⚠No built-in rate limiting — subject to Heroku API rate limits (1200 requests/hour per token)
⚠Stateless design — no persistent session management or operation queuing across MCP invocations
⚠No built-in encryption for sensitive values — config vars are base64-encoded in transit but stored plaintext in Heroku

Requirements

Node.js 16+ (MCP server runtime)Heroku API token (generated via `heroku auth:token` or OAuth)MCP client implementation (Claude Desktop, custom agent framework, or compatible tool)@heroku/mcp-server npm package installedHeroku API token with 'read' and 'write' scopes for target appsValid Heroku app name or IDMCP client with tool-calling supportHeroku API token with 'write' scope for dyno formation

Input / Output

Accepts: structured JSON parameters (app name, dyno type, config vars), natural language instructions (via Claude or LLM agent), environment variable references (HEROKU_API_TOKEN), key-value pairs (config variable names and values), JSON objects for bulk config updates, app identifiers (name or UUID), dyno type identifiers (standard-1x, standard-2x, performance-m, etc.), process counts (integer for number of dynos), app identifiers, git branch names or commit SHAs, release version numbers (for rollback operations), add-on service names, plan identifiers, configuration options (region, backup settings, etc.), time ranges (start/end timestamps), process type filters (web, worker, etc.), log source filters (app, system, etc.), app name (optional, auto-generated if not provided), region identifier, buildpack identifier, stack identifier (heroku-20, heroku-22, etc.), team identifiers, email addresses, role names (owner, collaborator, member)

Produces: structured JSON responses (app metadata, deployment status, resource info), operation confirmation messages, error details with Heroku API error codes, structured JSON with current config state, confirmation of config updates with timestamps, validation errors for invalid variable names or values, dyno formation status (current and target state), scaling operation confirmation with estimated completion time, error details if scaling fails (e.g., insufficient account credits), build status and logs, release information (version, timestamp, slug size), deployment progress indicators, error details with build failure reasons, add-on provisioning status, connection strings and credentials, plan details and pricing information, attachment confirmation, log lines with timestamps and process information, dyno metrics (memory, CPU, load average), app status (running, crashed, etc.), error summaries and stack traces, app creation confirmation with app ID and URL, app configuration details (region, buildpack, stack), deletion confirmation, error details if creation/deletion fails, collaborator list with roles and permissions, access grant/revoke confirmation, team membership information, error details if access change fails

UnfragileRank

Adoption41%(30% weight)

Quality17%(25% weight)

Ecosystem36%(25% weight)

Match Graph10%(15% weight)

Freshness75%(5% weight)

UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.

Type: MCP Server

8 capabilities

Visit @heroku/mcp-server→

Package Details

npm

Registry

1.2.1

Version

5,340

Weekly Downloads

About

Heroku Platform MCP Server

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Capabilities8 decomposed

heroku app lifecycle management via mcp protocol

Medium confidence

Solves for

Best for

DevOps engineers building AI-assisted deployment workflows

Solo developers automating Heroku app management through Claude

Teams integrating Heroku into LLM-powered CI/CD pipelines

Requires

Node.js 16+ (MCP server runtime)

Heroku API token (generated via `heroku auth:token` or OAuth)

MCP client implementation (Claude Desktop, custom agent framework, or compatible tool)

Limitations

Requires valid Heroku API token with appropriate OAuth scopes — no built-in token refresh or rotation

MCP protocol overhead adds ~100-200ms per request vs direct REST calls

Limited to operations exposed by Heroku Platform API v3 — advanced features like private spaces require additional configuration

What makes it unique

vs alternatives

heroku app configuration and environment variable management

Medium confidence

Solves for

Best for

Platform engineers managing configuration across multiple Heroku apps

DevOps teams automating secret rotation and config updates

Developers building self-service app configuration tools with AI

Requires

Heroku API token with 'read' and 'write' scopes for target apps

Valid Heroku app name or ID

MCP client with tool-calling support

Limitations

No built-in encryption for sensitive values — config vars are base64-encoded in transit but stored plaintext in Heroku

Bulk config updates are not atomic — partial failures may leave apps in inconsistent state

No change history or rollback mechanism — requires external versioning to track config changes

What makes it unique

vs alternatives

heroku dyno and resource scaling via agent instructions

Medium confidence

Solves for

Best for

DevOps teams automating cost optimization through dynamic scaling

Startups building self-healing infrastructure with AI agents

Teams implementing auto-scaling policies driven by monitoring data

Requires

Heroku API token with 'write' scope for dyno formation

Valid app name and process type (web, worker, etc.)

MCP client with tool-calling capability

Limitations

Scaling operations are not instantaneous — dyno restarts typically take 10-30 seconds, during which app is briefly unavailable

No built-in cost estimation — agents must reference external pricing data to make cost-aware scaling decisions

Scaling down may cause data loss if apps maintain in-memory state — no automatic persistence layer

What makes it unique

vs alternatives

heroku app deployment and release management

Medium confidence

Solves for

Best for

Teams automating CI/CD pipelines with AI-driven deployment decisions

DevOps engineers building intelligent rollback mechanisms

Developers implementing self-service deployment workflows

Requires

Heroku API token with 'write' scope for builds and releases

Git repository configured with Heroku remote or GitHub integration enabled

Valid app name and branch/commit reference

Limitations

Requires Heroku git remote or GitHub integration — cannot deploy arbitrary code without prior setup

Build times vary (2-10 minutes) — agents must handle async operations and polling for completion

No built-in health check integration — rollback decisions must be made by external monitoring systems

What makes it unique

vs alternatives

heroku add-on provisioning and lifecycle management

Medium confidence

Solves for

Best for

Platform engineers automating infrastructure provisioning

Startups building self-service app creation workflows

Teams managing add-on lifecycle at scale

Requires

Heroku API token with 'write' scope for add-ons

Valid app name

Add-on service identifier (e.g., heroku-postgresql, heroku-redis)

Limitations

Add-on provisioning is asynchronous — typically takes 30 seconds to 5 minutes, requires polling for completion

Plan upgrades may cause brief service interruptions — no zero-downtime upgrade option for most add-ons

Deprovisioning is destructive and irreversible — no built-in backup or recovery mechanism

What makes it unique

vs alternatives

heroku app monitoring and log retrieval via mcp

Medium confidence

Solves for

Best for

DevOps teams building AI-assisted troubleshooting workflows

Developers debugging production issues through natural language queries

Teams implementing intelligent alerting based on log analysis

Requires

Heroku API token with 'read' scope

Valid app name

MCP client with streaming or polling support

Limitations

Log retention is limited to 1500 lines per app — historical analysis requires external log aggregation

Metrics API has 1-minute granularity — fine-grained performance analysis requires external monitoring tools

Log streaming is not real-time through MCP — agents see batched logs with potential 30-60 second delay

What makes it unique

vs alternatives

heroku app creation and deletion with configuration

Medium confidence

Solves for

Best for

Platform teams automating app provisioning workflows

Startups building self-service app creation for users

DevOps engineers managing multi-app deployments

Requires

Heroku API token with 'write' scope for app creation/deletion

Unique app name (or auto-generation strategy)

Valid region identifier (us, eu, etc.)

Limitations

App creation is asynchronous — typically takes 5-10 seconds, requires polling for completion

App names must be globally unique across Heroku — agents must handle naming conflicts and retry logic

Deletion is irreversible — no built-in backup or recovery mechanism for deleted apps

What makes it unique

vs alternatives

heroku team and collaborator management

Medium confidence

Solves for

Best for

Platform teams managing access control at scale

Organizations implementing least-privilege access policies

DevOps teams automating onboarding/offboarding workflows

Requires

Heroku API token with 'write' scope for team and collaborator management

Valid app name or team identifier

Email address of user to grant/revoke access

Limitations

Role-based access control is limited to owner, collaborator, and member — no fine-grained permission scoping

Access changes are immediate — no approval workflow or staged rollout mechanism

No built-in audit logging — access changes must be tracked externally

What makes it unique

vs alternatives

More auditable than manual access management because agents can log all access changes and enforce consistent role assignment policies, reducing human error in permission management.

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

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@heroku/mcp-server

Capabilities8 decomposed

heroku app lifecycle management via mcp protocol

heroku app configuration and environment variable management

heroku dyno and resource scaling via agent instructions

heroku app deployment and release management

heroku add-on provisioning and lifecycle management

heroku app monitoring and log retrieval via mcp

heroku app creation and deletion with configuration

heroku team and collaborator management

Related Artifactssharing capabilities

@heroku/mcp-server

Monoid

mcp-agent

Kubernetes

network-ai

mcp-use

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Package Details

About

Categories

Alternatives to @heroku/mcp-server

Are you the builder of @heroku/mcp-server?

Get the weekly brief

Data Sources

@heroku/mcp-server

Capabilities8 decomposed

heroku app lifecycle management via mcp protocol

heroku app configuration and environment variable management

heroku dyno and resource scaling via agent instructions

heroku app deployment and release management

heroku add-on provisioning and lifecycle management

heroku app monitoring and log retrieval via mcp

heroku app creation and deletion with configuration

heroku team and collaborator management

Related Artifactssharing capabilities

@heroku/mcp-server

Monoid

mcp-agent

Kubernetes

network-ai

mcp-use

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Package Details

About

Categories

Alternatives to @heroku/mcp-server

Are you the builder of @heroku/mcp-server?

Get the weekly brief

Data Sources