Meshery API

Name: Meshery API
Brand: Meshery API
Availability: InStock

★ Only Publicly Available OpenAPI DocumentCloud InfrastructureContainer OrchestrationapiKey170 EndpointsREST

For Agents

Manage Meshery applications, designs, environments, connections, and performance profiles through 170 endpoints.

Install Jentic One Beta

Connect the Meshery API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Meshery API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with Meshery API.

Upload, deploy, and remove Meshery application files for declarative workload rollouts

Manage environments and the connections registered to each environment for multi-cluster setups

Share designs, filters, and other content between teams using the dedicated share endpoints

GET STARTED

Start building with Meshery API

Explore with Jentic

View OpenAPI Document

Jentic publishes the only available OpenAPI specification for Meshery API, keeping it validated and agent-ready. Meshery is the open-source cloud-native management plane for service meshes and Kubernetes, used to design, deploy, and operate workloads across multiple clusters and meshes. The 170-endpoint API spans application files, environments, connections, designs, filters, performance profiles, smart provisioning, and content sharing, exposing the operations needed to drive Meshery from CI pipelines, custom dashboards, or automation agents.

Use Cases

Patterns agents use Meshery API for, with concrete tasks.

★ GitOps-Style Application Rollouts

Platform teams using Meshery to manage cloud-native workloads can wire CI pipelines into the application endpoints to upload manifests with POST /api/application/{sourcetype} and roll them out via POST /api/application/deploy. DELETE /api/application/{id} and DELETE /api/application/deploy handle teardown for ephemeral environments, supporting GitOps-style rollouts across clusters.

Call POST /api/application/{sourcetype} to upload the manifest, then POST /api/application/deploy to roll it out to the target environment.

Multi-Environment Connection Management

Operators running Meshery across multiple clusters and meshes can model each as a Meshery environment and attach the relevant connections (Kubernetes contexts, mesh adapters) using POST /api/environments and POST /api/environments/{environmentID}/connections/{connectionID}. The corresponding GET and DELETE operations support inventory and cleanup as the topology evolves.

Call POST /api/environments to create a staging environment and POST /api/environments/{environmentID}/connections/{connectionID} to attach the staging Kubernetes connection.

Design Sharing Across Teams

Internal platforms can let teams reuse Meshery designs and filters by routing them through POST /api/content/design/share and POST /api/content/filter/share. This keeps reference architectures discoverable inside the organisation without forcing teams to copy YAML between repositories.

Call POST /api/content/design/share with the design ID to publish a reference design to the platform team's catalogue.

Performance Profiling Workflow

Reliability teams can run Meshery performance profiles to characterise workload and mesh behaviour, surface regressions before deploys, and hand the resulting profiles back to designers as inputs for sizing decisions. The performance endpoints in the API drive both the run and the retrieval of the resulting reports.

Trigger a performance profile run against the staging environment and retrieve the resulting report for the on-call review.

Agent-Driven Mesh Operations

An AI agent embedded in a platform team's workflow can take instructions like 'deploy the new app to staging', 'list the connections in the prod environment', or 'share this design with the SRE team'. Through Jentic the agent finds the matching Meshery operation, loads the schema, and executes it without writing custom Meshery client code.

Search Jentic for 'deploy a Meshery application', load POST /api/application/deploy, and execute it with the application ID and environment from the user's instruction.

Key Endpoints

170 endpoints — jentic publishes the only available openapi specification for meshery api, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

POST

/api/application/{sourcetype}

Upload a Meshery application file

POST

/api/application/deploy

Deploy a Meshery application

DELETE

/api/application/deploy

Undeploy a Meshery application

DELETE

/api/application/{id}

Delete a Meshery application file

GET

/api/environments

List Meshery environments

POST

/api/environments

Create a new environment

POST

/api/environments/{environmentID}/connections/{connectionID}

Attach a connection to an environment

POST

/api/content/design/share

Share a Meshery design

POST

/api/application/{sourcetype}

Upload a Meshery application file

POST

/api/application/deploy

Deploy a Meshery application

DELETE

/api/application/deploy

Undeploy a Meshery application

DELETE

/api/application/{id}

Delete a Meshery application file

GET

/api/environments

List Meshery environments

Why Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Meshery session credentials are stored in the Jentic vault. Agents call the API with a scoped Jentic token and Jentic attaches the token cookie at the gateway, so raw session credentials never enter the agent context.

Intent-based discovery

Agents search Jentic with intents like 'deploy a Meshery application' or 'list Meshery environments' and receive the matching application, environment, or design operation with its request schema.

Time to first call

Direct Meshery integration: 1-2 weeks across the 170 endpoints to cover applications, environments, designs, and performance profiles. Through Jentic: a few hours per workflow.

FAQs

Specific to using Meshery API through Jentic.

Why is there no official OpenAPI spec for Meshery API?

Meshery does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Meshery API via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.

What authentication does the Meshery API use?

Meshery authenticates via a session cookie named token, set after the user signs in to the Meshery server. Through Jentic, that session credential is stored in the credential vault and the agent calls the API with a scoped Jentic token rather than handling the cookie directly.

Can I deploy and undeploy applications with the Meshery API?

Yes. POST /api/application/deploy rolls out an application to its target environment and DELETE /api/application/deploy tears it down. The application file itself can be removed with DELETE /api/application/{id} when it is no longer needed.

What are the rate limits for the Meshery API?

The OpenAPI spec does not declare explicit rate limits. Meshery is typically self-hosted, so limits depend on the deployment; high-volume CI use should sequence calls per environment and back off on 5xx responses to avoid overloading the Meshery server.

How do I share a Meshery design through Jentic?

Install the SDK with pip install jentic, search for 'share a Meshery design', load the POST /api/content/design/share operation, and execute it with the design ID. Jentic attaches the session credential and posts to the Meshery server.

Does the Meshery API support multi-environment connections?

Yes. Environments are first-class resources via /api/environments, and connections are attached using POST /api/environments/{environmentID}/connections/{connectionID}. This is how Meshery models multiple clusters or meshes under a single management plane.

Meshery API

Connect the Meshery API to your agent

Capabilities

Start building with Meshery API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs