JoLink

joLink Runtime

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A lightweight, headless Java IDE for AI coding agents.

Closing the loop for autonomous Java development.

Design principle: Everything exists to reduce uncertainty for the LLM.

joLink does not provide an editor UI. Instead, it exposes incremental compilation, testing, application startup and breakpoint debugging through MCP to the coding agent you already use—so it can run the code, inspect real state, and verify its own changes.

Persistent compilation state and HotSwap reduce repeated full rebuilds and JVM restarts. When tests, logs and endpoint responses are not enough, the agent can use breakpoints and inspect exception events, stack frames and variables.

Free and local. It does not require a joLink account, model API key, inference provider, or separate agent application.

Install

1. Open a new chat in your coding agent.
2. Click the copy button in the code block below, paste the entire prompt into that chat, and send it.

Follow this guide:
https://github.com/L1ch404/jolink-runtime/blob/main/INSTALL.md
Install joLink MCP and its English Skill for my current agent.
Enable the global Java change-verification rule for this agent across projects.
Use user-level installation by default and preserve existing configuration.
Check the saved configuration, Skill and rule. If a client UI action or reload is needed,
stop and tell me what to do; leave connection and rule-loading verification to a chat after reloading.

3. If the agent reports that a reload is needed, reconnect MCP or restart the client as instructed, then open a new chat. Configuration complete but not yet loaded is not an installation failure. In the loaded chat, you can send:

Verify the existing joLink MCP and jolink-java Skill in this client without reinstalling them.
Call the joLink status tool exposed by this client once, and check its Skill list or loading facility.
If I enabled it, also check whether the global Java change-verification rule is loaded through the client's native instructions view.
If anything is unavailable or its loading cannot be confirmed, report it and stop; do not write a standalone verification script.
Do not start applications or run tests.

The guide provides official client-specific locations and examples for Codex, Claude Code, Cursor, VS Code/Copilot, CodeBuddy, Gemini CLI, OpenCode, Cline, Roo Code, Windsurf and Kiro. All start MCP with uvx jolink-runtime@latest and use the same English Skill; no plugin bundle or universal installer is required. MCP performs the work; the Skill explains the workflows; the optional global verification rule makes proportionate Java verification part of implementation tasks across projects. The prompt above explicitly enables it; remove that line if you only want MCP and the Skill. The guide also covers uv setup, preserving configuration, reconnection and verification.

For Chinese instructions, use the Chinese installation guide.

Why joLink

Coding agents are good at reading and changing code, but they can become stuck in a loop of static assumptions:

analyze
-> patch
-> assume the patch works
-> patch again

joLink adds the missing runtime feedback loop:

analyze
-> change
-> run
-> observe
-> update the hypothesis
-> change again if necessary

This is useful when:

• the Java application is not running yet;
• a code change needs to be verified against real behavior;
• repeated patches have not solved the problem;
• endpoint results do not match the source-code interpretation;
• logs or tests are insufficient to explain the executed path;
• business naming is inconsistent and static search cannot find the relevant code;
• deeper runtime evidence such as breakpoints, stacks, or variables is needed.

The goal is not to use a debugger for every problem.

Start with the cheapest useful evidence:

application status
-> logs and actual outputs
-> exception events
-> executed path
-> breakpoints, stack frames, and variables

Debug deeper only when necessary.

What it can do

joLink exposes four focused MCP tools:

• java_application — project launch, compile-aware restart (HotSwap by default), stop, and attach;
• java_fast_test — selected Java tests, result details and cancellation, without an application launch;
• java_status — Java process discovery, compact status, on-demand details and logs;
• java_debugger — breakpoints, exception events, stacks, variables, and resume.

After editing a managed project, call java_application(action=restart). It incrementally compiles changes in the existing JDT workspace and prefers HotSwap; incompatible changes restart the JVM using those same compiled outputs. Set hotswap=false to force process/application reinitialization. The result's apply_method distinguishes HotSwap from a real restart. See restart workflow.

Fast Test uses a Maven or Gradle Probe only when its small configuration cache is absent or changed. The exported test Build World and JDT workspace persist across MCP processes. JDT keeps main and test classes current and runs explicit JUnit 4/5 or TestNG tests in an isolated JVM:

java_fast_test(action=run,
  project_path=/path/to/project,
  source_files=[src/main/java/example/Service.java],
  tests=[example.ServiceTest#works], timeout=60)
-> if unfinished, choose a suitable waiting interval, then call java_status(action=status)
-> read diagnostics/failures with java_fast_test(action=result, test_run_id=...)
-> cancel with java_fast_test(action=cancel, test_run_id=...)

java_status(status).fast_test stays compact. If compilation fails before run returns, its reply includes compiler diagnostics directly. Errors that occur after a timeout reply and failed-test details are available through result; follow the summary's next_action or use its test_run_id, without rerunning tests. Full compiler file lists are omitted. Only the active and most recently completed test attempts are retained in the current MCP session; an unavailable ID returns TEST_RUN_NOT_FOUND.

passed=false means the selected tests executed and found a failure; it is not a Tool infrastructure error. Fast Test does not require or modify a running application. The current JDT supports Java 8 through 26 source/target levels; product regression covers 8, 11, 17 and 21, including separate main/test levels. Target libraries and application/test JDKs still follow the project. Supported build layouts include Maven jar projects, one explicitly selected jar module in a standard Reactor, and Gradle Java builds including multi-Project dependencies (tested with 7.4.2, 8.10 and 8.14). Maven and Gradle multi-module launch and Fast Test resolve the selected module's upstream dependencies into separate JDT projects in one Worker. Unchanged modules reuse their output; JavaBuilder propagates changed APIs and constants to affected downstream sources. Local module dependencies use current workspace output rather than installed JARs; Maven also supports test-jar dependencies. See Gradle multi-module flow and evidence.

Demo

From an unexpected API response to runtime investigation.

Reading source code tells an agent what might happen. Running the application and inspecting its state helps the agent check what actually happens.

The screenshots below show a debugging example: an agent starts a Java application, checks an endpoint, notices an unexpected result, and uses joLink to investigate the execution path.

This is a constructed demonstration scenario, not a record of an actual business incident. Some sensitive information in the screenshots has been redacted for privacy.

1. Start the application and check the actual response

The agent uses java_application to launch the application and java_status to check its state, then sends an HTTP request to a sample risk-scoring endpoint.

For score=80, the expected category is High Risk, but the agent reports Medium Risk. It checks additional boundary values before investigating further.

2. Set a breakpoint and inspect runtime variables

The agent uses java_debugger to set a breakpoint on the Medium Risk branch, triggers another request, and inspects the variables after the breakpoint is hit.

The conversation shows score=80 while execution is in the Medium Risk branch. This gives the agent runtime evidence to investigate its boundary-condition hypothesis, rather than relying only on source-code assumptions.

This example demonstrates application startup and runtime investigation. It is not a Fast Test performance benchmark; the screenshots cover the investigation stage, not the subsequent fix and re-verification.

Private diagnostics

joLink keeps stdout exclusively for MCP JSON-RPC. Python lifecycle logs and tracebacks are also written to a bounded private rotating file:

Windows: %LOCALAPPDATA%\jolink-runtime\logs\mcp.log
macOS/Linux: $XDG_CACHE_HOME/jolink-runtime/logs/mcp.log
               or ~/.cache/jolink-runtime/logs/mcp.log

status does not return mcp.log paths or logging configuration, even with details=true. Read the local file at the path above when diagnosing joLink itself. A diagnostic-file failure never prevents the MCP server from starting. The file is limited to 4 MiB with three rotated backups; stdout remains untouched.

java_status(action=status) is a compact overview: readiness, process/debug state, active operation and recent restart/Test summaries. Read java_status(action=status, details=true) for current launch errors, full last_reload, compiler/cache settings and timings. Completed launch/restart calls already return their own detailed result; the flag is useful when an operation continued after the synchronous reply timeout. Neither call reads or embeds build logs. Use java_status(action=logs, source=build) for the current launch's build log, or omit source to read application output; both accept tail. Restart summaries include a next_action pointing to details.

launch/restart replies include previous_startup_ms: the prior successful JVM startup duration saved locally for the same launch, captured before the new operation. It excludes Probe/JDT compilation. With ready_port it measures startup through observed TCP readiness; otherwise it only measures JVM/ JDWP startup. HotSwap and failed startups do not replace this observation. It is written once when startup succeeds to a small JSON file under the joLink cache's startup-timings/ directory. Stop, a new conversation or an MCP restart does not discard it. The next launch reads that file; no expiry, build-input validation or repeated status writes are involved. An unseen launch returns null. Treat it as a waiting reference, not a prediction or a readiness check.

Set JOLINK_LOG_LEVEL in the MCP server's environment and restart it: WARNING (default) keeps warnings/errors only; INFO records JDT cache/source/build/save summaries and native FULL fallback reasons; DEBUG also retains detailed Worker output; ERROR keeps errors only; OFF disables joLink diagnostic logging. Application logs and tool results are unaffected. The Worker uses a fixed incremental propagation limit of 10 rounds. See JDT build diagnostics.

The public actions are:

launch
stop
restart
attach
detach
breakpoint
exception
wait_event
threads
stack
variables
resume
cleanup_debug_state
processes / status / logs

These actions support:

• launching a Java application as an owned JVM process;
• launching a Maven/Gradle project with project_path and main_class, or optionally importing an IntelliJ IDEA Application/Spring Boot configuration, exporting its Build World without running Maven/Gradle compilation, compiling with JDT before JVM startup, and launching without packaging a fat JAR;
• stopping or restarting an application after code changes;
• compiling detected edits in a persistent private JDT session and applying compatible loaded class definitions with HotSwap;
• inspecting application status and logs;
• attaching to an already-running local JVM;
• setting semantic breakpoints and exception watches;
• waiting for runtime events;
• inspecting threads, stack frames, and variables;
• resuming suspended execution;
• cleaning up debug state safely.

Current status

Current package version:

0.1.0a9

Status:

Alpha / controlled dogfood

The first adapter targets local Java applications through JDWP.

The current MCP implementation includes:

• stdio transport;
• stdout reserved exclusively for MCP protocol messages;
• JSON TextContent with matching structuredContent;
• Runtime ok=false mapped to MCP isError=true;
• cancellable wait_event;
• optional two-phase waiting with arm and await;
• an optional loopback HTTP trigger started only after JDWP is armed, with a one-call blocking shortcut or explicit arm/await;
• wait-scoped JDWP requests;
• ownership-aware shutdown;
• automatic cleanup and resume paths;
• persistent JDWP packet framing across short polling timeouts.

The current two-phase implementation is intended for controlled dogfood. Known cancellation, cleanup-preemption, handle-publication, and response delivery limitations are tracked in:

docs/stage-2.1.2-lifecycle-backlog.md

Do not use this alpha release for unattended production JVM debugging.

Requirements

• JDK 8 or newer
• uv

uv manages the Python environment automatically. A separate Python installation is normally not required.

Confirm the requirements with:

java -version
uv --version

Quick start

After the MCP server is connected, confirm that these tools are available:

java_application
java_fast_test
java_status
java_debugger

Open a local Java project and ask the coding agent:

Use joLink to start this Java application, inspect its status and logs,
and verify the latest code changes against real runtime behavior.

For a problem that has already survived multiple attempted fixes:

Do not apply another speculative patch yet.

Use joLink to run the current Java application and collect actual runtime
evidence. Start with status, logs, tests, and actual outputs. Re-evaluate the
root-cause hypothesis before changing the code again.

For deeper investigation:

Use joLink to reproduce this issue.

Start with actual outputs and logs. If that evidence is insufficient, use a
breakpoint or exception watch, inspect the relevant stack frames and variables,
then resume or clean up the suspended JVM.

joLink starts and observes the Java application. The coding agent may use its normal HTTP, terminal, browser, or testing tools to trigger the scenario.

For a method-body edit in an application launched with project_path, the agent can avoid a full Maven rebuild/restart:

java_status(action=status; confirm runtime_active and compile_ready=true)
-> java_application(action=restart)
-> if still running, java_status(action=status; observe last_reload)
-> trigger a fresh request
-> verify the new runtime behavior

restart automatically detects and incrementally compiles source changes, then uses HotSwap by default. Deleted/unloaded classes, generated resource changes or explicit JVM rejection select a real restart using those already compiled outputs. hotswap=false forces process reinitialization. No pending code changes restart without compiling. Compilation errors leave the old process running. Lost HotSwap replies remain unknown rather than being mistaken for explicit rejection. The call waits up to timeout (maximum 30 seconds); if unfinished, it returns restart_started plus the existing reload_id, observable through active_operation and last_reload. apply_method distinguishes HotSwap from process restart. Completed builds immediately save JDT state and source indexes in the local persistent workspace. There are no extra class-output copies. HotSwap does not rerun initialization or refresh Spring metadata; verify with a fresh request. Breakpoints in redefined classes become stale and must be reset.

The locked JDT Worker is installed into a content-addressed user cache on first use. Valid Eclipse bundles are reused from older joLink caches; missing bundles are downloaded and verified, while the product Worker and Equinox configuration ship inside the Python package. A changed build configuration or unavailable session refreshes via the existing project launch path. Use restart(hotswap=false) when startup/framework state must be recreated.

The product uses Eclipse 4.40 / JDT 3.46 with matching APT bundles. Its Worker targets Java 17 bytecode and defaults to a private, pinned Temurin 21 runtime, installed once in the user cache. Maven/Gradle and application/test JVMs keep their project JDKs. JOLINK_WORKER_JAVA_HOME can select a corporate-provided 64-bit JDK 17+ instead. Old Lombok 1.18.20 compatibility issues remain recorded, not silently fixed by replacing project dependencies. See JDT 3.46 and private Worker JDK for offline setup and actual compatibility results.

First-time JDK/Eclipse downloads use their pinned official URLs by default. Set JOLINK_DOWNLOAD_MIRROR=cn to try TUNA, then the joLink mirror at https://7355608.net/jolink/assets, then upstream on connection/transfer failure. A custom mirror base URL uses that mirror followed by upstream; official (or an empty value) uses upstream only. No IP/geolocation detection is performed. Existing SHA256 checks and installed caches are unaffected. TUNA access was blocked during local verification; selecting cn does not guarantee its availability. See runtime mirror setup.

The imported IDEA Make/Build flag does not cause Maven or Gradle compilation. On the first launch, the Probe exports compiler/runtime facts and JDT performs FULL compilation. Later launches reuse the persisted Probe model and use saved source size/mtime to detect edits. Changes to tracked Maven/Gradle configuration refresh the model. Untracked external scripts and hidden inputs remain recorded in the compatibility follow-up; cache deletion is not a routine startup or installation step.

See JDT-first startup for the current single-module startup and cache behavior.

Typical workflow

A normal verification flow looks like this:

read the code
-> change the code
-> java_application(launch or restart, ready_port=<application port>)
-> if startup_state=starting, call java_status(status) until ready
-> if startup_state=failed, inspect java_status(logs)
-> trigger a test or endpoint
-> inspect the actual result
-> update the diagnosis

A deeper debugging flow looks like this:

run or attach
-> for an owned HTTP application, confirm startup_state=ready
-> configure a breakpoint or exception watch
-> for a managed local HTTP request:
   wait_event(wait_mode=blocking, http_trigger=...)
-> otherwise:
   wait_event(wait_mode=arm)
   -> trigger the scenario after status=armed
   -> wait_event(wait_mode=await, wait_handle=...)
-> inspect stack frames and variables
-> resume or cleanup_debug_state

For a local HTTP endpoint, blocking composes the existing arm -> trigger -> await lifecycle into one call:

{
  "action": "wait_event",
  "wait_mode": "blocking",
  "timeout": 30,
  "http_trigger": {
    "method": "POST",
    "url": "http://127.0.0.1:8080/example",
    "json_body": {"id": 1},
    "timeout_seconds": 30
  }
}

Use explicit arm followed by await when an external action must occur between arming and observation. A terminal result consumes its wait_handle; the handle observes Runtime events and is not an HTTP-response handle.

For an HTTP application launched by joLink, distinguish process/debugger startup from application TCP readiness:

{
  "action": "launch",
  "jar_path": "target/app.jar",
  "jdwp_port": 5005,
  "ready_port": 8080,
  "timeout": 30
}

For java_application(launch/restart) and java_fast_test, timeout limits the synchronous result wait, including runtime preparation and compilation. It defaults to 30 seconds; larger values are accepted but wait only 30 seconds. Zero returns after task submission. The original task continues after this reply deadline. Test Runner execution has a separate internal 300-second limit; timeout no longer configures it. If still running, choose a waiting interval appropriate to the stage (for example using sleep or PowerShell Start-Sleep), then query java_status. Do not rapidly poll or resubmit the task. The old readiness-wait argument has been removed, not retained as an alias. Direct JAR/classpath launches still perform their existing process creation and JDWP handshake before returning a task observation. timeout=0 skips the additional readiness wait; it does not make that initial handshake asynchronous. If the process is alive but the application port is not accepting connections, the result remains successful with startup_state=starting; the process is kept alive and next_action=status. Each later status call probes the stored port again. startup_state=ready means only that the configured loopback TCP port accepted a connection; it does not prove that every dependency, cache, or business endpoint is healthy.

When ready_port is omitted, joLink reports startup_state=unverified rather than claiming application readiness. An HTTP trigger remains allowed for attached and otherwise unverified JVMs, but its result includes a warning. When configured readiness is still starting, joLink rejects an HTTP trigger without sending it.

Runtime safety

joLink 0.1.0a9 is designed for local, trusted development environments.

Current safety boundaries:

• MCP transport is stdio;
• JDWP access is limited to local JVMs;
• one joLink server controls one Java target at a time;
• a JVM launched by joLink is treated as an owned process;
• an owned JVM may be stopped by joLink;
• an externally started JVM is attached, resumed, and detached;
• an attached JVM is never intentionally terminated;
• raw JDWP requests are armed only while a waiter owns them; logical breakpoint and exception definitions persist until removed or cleaned up;
• built-in HTTP triggers accept only http://127.0.0.1, do not use environment proxies or redirects, and never return the request URL, headers, body, or their raw values in validation errors;
• a configured ready_port must be unused before launch and must differ from the JDWP port; the TCP probe is local and does not send an application request;
• response_headers_received reports only the HTTP status/response headers; joLink does not read or return the response body;
• cancelling an HTTP client wait closes joLink's side of the connection but cannot guarantee that server-side business work has been undone;
• successful cleanup_debug_state includes its own debug-state verification; a separate HTTP cleanup state may remain settling without delaying JVM cleanup;
• after receiving a suspension_id, the agent must call resume or cleanup_debug_state.

Do not expose the JDWP port to an untrusted network.

Do not use the current alpha release for remote or production debugging.

Client notes

CodeBuddy

Some current CodeBuddy environments may initially display:

Description: No description

Use the host's tool-definition loading/search facility to obtain the actual schema. Do not infer arguments from a tool name alone. The independently installed jolink-java Skill provides a discovery and workflow entry point; it does not replace the MCP connection or guarantee tool selection. Follow the installation guide for the specific CodeBuddy surface (CLI, IDE or editor plugin), rather than assuming their configuration files are interchangeable.

Development

Clone the repository and install development dependencies:

uv sync --extra dev --locked

Run the default test suite:

uv run pytest

Run the stdio server from the source checkout:

uv run jolink-runtime

Equivalent module entry point:

uv run python -m jolink_runtime.transport.stdio

A generic MCP client configuration can launch it directly from a checkout:

{
  "mcpServers": {
    "jolink-runtime": {
      "command": "uv",
      "args": [
        "--directory",
        "/absolute/path/to/jolink-runtime",
        "run",
        "jolink-runtime"
      ]
    }
  }
}

Tests

After changing joLink source, do not kill an MCP server and assume an existing host tool handle will reconnect. Start a fresh server from the current worktree through the real stdio protocol:

uv run python scripts/jolink_mcp_dev_client.py

The client prints the Git commit, dirty-worktree state, source fingerprint, Python executable, and stderr path before accepting JSONL tools/call requests. Send {"command":"quit"} to close the client and trigger normal server cleanup. This is the canonical interactive verification path for uncommitted code; a Codex/IDE MCP connection should be established only after the code under test is frozen.

The real subprocess acceptance test exercises the MCP stdio boundary:

uv run pytest -q tests/e2e/test_stdio_mcp.py

It performs:

initialize
-> tools/list
-> java_status(status)
-> close the stdio client
-> wait for the server process to exit

The heavier real MCP/JVM suite is opt-in locally:

JOLINK_RUN_MCP_JAVA_E2E=1 \
  uv run pytest -q -m mcp_java_e2e tests/e2e/test_stdio_mcp_java.py

The managed Temurin 21 Worker and Java 8 application lifecycle have standalone deep validators (Worker JDK and application/target JDK are different roles):

uv run python scripts/validate_jdt_worker_matrix.py \
  --target-java-home <jdk8> \
  --worker-java-home <jdk21>

uv run python scripts/validate_jdt8_product_mcp.py \
  --jdk8-home <jdk8> \
  --maven-home <maven-home>

JOLINK_RUN_FAST_TEST_E2E=1 \
JOLINK_FAST_TEST_JAVA8_HOME=<jdk8> \
  uv run pytest -q -m fast_test_e2e \
  tests/e2e/test_fast_test_product.py

uv run python scripts/validate_fast_test_build_jdk_matrix.py \
  --target-java8-home <jdk8> \
  --build-java-home <jdk8> \
  --build-java-home <jdk11> \
  --build-java-home <jdk17>

uv run python scripts/build_jdt_worker_release.py \
  --java-home <jdk8> \
  --maven <maven-executable> \
  --gradle <gradle-executable>

The canonical CI environment for the heavier suite is:

Linux
Python 3.11
Application/target JDK 8/11/17/21; managed Worker JDK 21

Contracts

See current documentation, product Java sources and builds, and historical research records. Archived experiment commands and limits are not the current product interface.

• MCP v0.1: docs/mcp-contract-v0.1.md
• Runtime lineage 2.4.0: docs/runtime-lineage-contract-2.4.0.md

License

joLink's own code is MIT-licensed. Downloaded Eclipse/Temurin runtimes and installed Python dependencies retain their own licenses. See third-party notices and corresponding sources. Offline runtime kits must be accompanied by the matching source kit and notices.