Provides AI agents with structured Windows state including processes, windows, and UI trees using JSON instead of expensive screenshots.
Also known as aipm-engine/AIPM, aipm, aipm-mcp-server
- Stars
- 1
- Tools
- 28
- Downloads, 30 days
- —
- Latest version
- 0.5.0
- Last commit
- Sep 18, 2026
- License
- MIT
What is AI Process Manager MCP?
AI Process Manager provides AI agents with structured Windows state including processes, windows, and UI trees using JSON instead of expensive screenshots. It exposes 28 tools, such as aipm_ja_faz, health_check, check_process.
Summary generated from the project's README
About AI Process Manager MCP server
AI Process Manager (AIPM) provides AI agents with a structured view of the Windows operating system using JSON and text instead of expensive screenshots. This approach significantly reduces token consumption, using roughly 15 to 150 tokens per query compared to the thousands required for pixel data. It is designed for developers using MCP clients like Claude Desktop or Cursor to build agents that can perceive and interact with a local machine.
To use this server, the AIProcessManager.exe backend must be running in the Windows system tray. The server connects to the local HTTP API via loopback, ensuring data stays on the machine. Users can configure the agent identity using the AIPM_AGENT_NAME environment variable to distinguish between multiple agents in the audit logs. The system includes a variety of tools for checking processes, reading window text, inspecting UI trees, and performing UI actions like clicking or typing.
Interaction is split into two categories: read-only perception tools and action tools. While perception tools like check_process or list_windows are generally available, UI actions such as ui_invoke or ui_set_value require explicit user opt-in through a tray menu and a per-app allowlist. This architecture allows agents to interact with background windows via UI Automation without stealing keyboard focus from the user.
What you can do with it
- 1Monitor running applicationsAn agent can verify if a specific software task is still active without needing to see the screen.
- 2Extract text from windowsA developer can instruct an agent to read the contents of a console or window directly as text.
- 3Automate background UI tasksAn agent can interact with elements in a window that is not currently in the foreground.
- 4Inspect complex application structuresAn agent can navigate deep UI hierarchies in Electron or Chromium-based applications.
Written from the project's README. Every use case is checked against a quote from it.
How to install AI Process Manager MCP
Formats verified 10 Nov 2026Add to CursorAdd to GooseInstall AI Process Manager MCP in Claude Code
$ claude mcp add aipm -- npx -y aipm-mcp-serverInstall AI Process Manager MCP in Cursor
~/.cursor/mcp.json
{
"mcpServers": {
"aipm": {
"command": "npx",
"args": [
"-y",
"aipm-mcp-server"
]
}
}
}Install AI Process Manager MCP in VS Code
.vscode/mcp.json
{
"servers": {
"aipm": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"aipm-mcp-server"
]
}
}
}Install AI Process Manager MCP in VS Code CLI
$ code --add-mcp '{"name":"aipm","type":"stdio","command":"npx","args":["-y","aipm-mcp-server"]}'Install AI Process Manager MCP in Claude Desktop
claude_desktop_config.json
{
"mcpServers": {
"aipm": {
"command": "npx",
"args": [
"-y",
"aipm-mcp-server"
]
}
}
}Install AI Process Manager MCP in Codex
$ codex mcp add aipm -- npx -y aipm-mcp-serverInstall AI Process Manager MCP in Codex config.toml
~/.codex/config.toml
[mcp_servers.aipm] command = "npx" args = ["-y", "aipm-mcp-server"]
Install AI Process Manager MCP in Gemini CLI
$ gemini mcp add -s user aipm npx -- -y aipm-mcp-serverInstall AI Process Manager MCP in Gemini settings.json
~/.gemini/settings.json
{
"mcpServers": {
"aipm": {
"command": "npx",
"args": [
"-y",
"aipm-mcp-server"
]
}
}
}AI Process Manager MCP tools 28
Detected from the READMEaipm_ja_fazhealth_checkcheck_processlist_processeslist_windowsget_system_statusget_taskbarread_windowget_ui_treewait_forget_recent_eventscheck_file
| aipm_ja_faz | — | |
| health_check | — | |
| check_process | — | |
| list_processes | — | |
| list_windows | — | |
| get_system_status | — | |
| get_taskbar | — | |
| read_window | — | |
| get_ui_tree | — | |
| wait_for | — | |
| get_recent_events | — | |
| check_file | — |
Show all 28 toolsShow fewer tools
get_app_knowledgeget_economy_statsget_audit_logread_notesui_findui_find_atui_actui_invokeui_set_valueui_send_keysui_dragui_select_optionfocus_windowreport_task_outcomereport_action_outcomepost_note
| get_app_knowledge | — | |
| get_economy_stats | — | |
| get_audit_log | — | |
| read_notes | — | |
| ui_find | — | |
| ui_find_at | — | |
| ui_act | — | |
| ui_invoke | — | |
| ui_set_value | — | |
| ui_send_keys | — | |
| ui_drag | — | |
| ui_select_option | — | |
| focus_window | — | |
| report_task_outcome | — | |
| report_action_outcome | — | |
| post_note | — |
Configuration
AIPM_AGENT_NAMEAIPM_APIAI Process Manager HTTP base URL (default: http://127.0.0.1:9147)
| Name | Description | |
|---|---|---|
| AIPM_AGENT_NAME | — | |
| AIPM_API | AI Process Manager HTTP base URL (default: http://127.0.0.1:9147) |
Automated checks
Ran Nov 14, 2026Full report →Passed our automated checks. That is not a security audit: read the code and give the server the narrowest access it needs. How checks work · What to fix for more points
- Source repository linked and reachableaipm-engine/aipm is public and reachablegithub.com/aipm-engine/aipm ↗Pass
- Package names this repository as its sourceaipm-mcp-server names git+https://github.com/agorapassadoagora-debug/AIPM.git as its sourcenpmjs.com/package/aipm-mcp-server ↗Finding
- Build provenance (Sigstore attestation)No build attestation published for this releaseNot checked
- Open source license (OSI)MITspdx.org/licenses/MIT.html ↗Pass
- Commit or release in the last yearLast commit or release 2026-09-18github.com/aipm-engine/aipm ↗Pass
- OpenSSF ScorecardNot checked
- Package name not close to a popular packageNo popular package one edit away from aipm-mcp-serverPass
- No critical advisory in the package or its dependencies1 resolved dependencies checked; no critical advisoryosv.dev ↗Pass
- No hidden instructions to the model28 tool descriptions and the README read; no override phrases, credential paths or hidden charactersPass
- Destructive tools are labelledNo tool named like delete, drop or execPass
- Remote endpoint answers the MCP handshakeNot checked
README
View on GitHubAI Process Manager — MCP Server
Structured Windows state for AI agents — no screenshots.
This MCP server exposes the AI Process Manager local HTTP API as tools for Claude Desktop, Cursor, and any MCP client. Instead of capturing pixels (~2,765 tokens per 1080p screenshot), agents read JSON and text (~15–150 tokens per query) from processes, windows, consoles, and UI Automation trees.
Requires: AIProcessManager.exe running on Windows (system tray). Node.js ≥ 14. Zero npm dependencies.
Why this exists
Computer-use agents often "look" at the desktop via screenshots. That is slow (3–5 s), expensive in tokens, and sends pixel data through the model. AIPM answers structured questions on loopback:
| Question | Screenshot | AIPM tool |
|---|---|---|
| Is the render still running? | ~2,765 tokens | check_process → ~15 tokens |
| What's the console output? | screenshot + OCR | read_window → ~30 tokens |
| Did the export finish? | poll + screenshots | wait_for(file_stable=...) → one call |
~94–98% fewer perception tokens per action vs screenshots (2,765 → ~60 tokens per query; the two inputs are the assumptions block of GET /analytics/summary, not a benchmark).
Quick start
1. Start the backend
Ensure AIProcessManager.exe is running in your system tray.
2. Configure your MCP client
Claude Desktop — claude_desktop_config.json:
{
"mcpServers": {
"ai-process-manager": {
"command": "node",
"args": ["C:\\path\\to\\ai-process-manager\\mcp\\server.js"]
}
}
}
Cursor and other stdio MCP clients take the same command / args pair. Optional env var
AIPM_API overrides the API base URL (default: read from
%LOCALAPPDATA%\AIProcessManager\endpoint.txt, else http://127.0.0.1:9147).
Optional env var AIPM_AGENT_NAME names this agent in the API's activity log (default mcp).
Every request is sent with User-Agent: AIPM-Agent/<name> (<client>) mcp:<client>, and the API
extracts <name> into the agent field of /audit, /activity and /notes. Use it when several
agents share one MCP client, so GET /activity can tell them apart:
"env": { "AIPM_AGENT_NAME": "revisor" }
The name is normalized to [a-z0-9._-], max 40 chars. It is an identity the caller declares about
itself — observability and coordination only, never authorization. Anyone can write any name here;
nothing in the product grants or denies permission based on it. The only barrier remains the
deny-by-default action allowlist, which is per app.
3. Restart the MCP client
Tools appear as ai-process-manager. Call health_check first.
Tools (28)
The 15 perception tools and the two UI probes are annotated readOnlyHint: true — clients may
auto-approve them. The seven UI actions are readOnlyHint: false and refuse to run unless the user
opts in (see Privacy).
| Tool | Title | Endpoint |
|---|---|---|
aipm_ja_faz |
Does the AIPM already do this? Ask before writing code or reaching for the shell | GET /?q= |
health_check |
Status + which action family to use + real-input arm state | GET / + GET /forgepilot/status |
check_process |
Check if a process is running | GET /processes |
list_processes |
List running processes | GET /processes |
list_windows |
List open windows | GET /windows |
get_system_status |
Get system status (CPU, RAM, GPU, disk) | GET /system |
get_taskbar |
Show taskbar apps | GET /taskbar |
read_window |
Read text from a window | GET /window/text |
get_ui_tree |
Get a window's UI element tree | GET /ui/tree |
wait_for |
Wait until a condition is met | GET /wait |
get_recent_events |
List recent PC events | GET /events/history |
check_file |
Check a file or folder | GET /filesystem/watch |
get_app_knowledge |
Get learned recipes for an app | GET /knowledge/app |
get_economy_stats |
Get token economy statistics | GET /analytics/summary |
get_audit_log |
View API audit log | GET /audit |
read_notes |
Read the local agent noticeboard | GET /notes |
UI tools — state first, then opt-in actions:
| Tool | Title | Endpoint |
|---|---|---|
ui_find |
Find interactive UI elements | GET /ui/find |
ui_find_at |
Find the UI element under a screen pixel | POST /ui/find_at |
ui_act |
Act by intent (decides UIA vs real input) | POST /ui/act |
ui_invoke |
Click a UI element | POST /ui/invoke |
ui_set_value |
Set the value of a UI field | POST /ui/set_value |
ui_send_keys |
Type text with synthetic keystrokes (last resort) | POST /ui/send_keys |
ui_drag |
Drag an element onto another | POST /ui/drag |
ui_select_option |
Select an option in a dropdown | POST /ui/select_option |
focus_window |
Bring a window to the foreground | POST /ui/focus |
Local telemetry (writes to the local store, metadata only):
| Tool | Title | Endpoint |
|---|---|---|
report_task_outcome |
Report task outcome (telemetry) | POST /telemetry/task |
report_action_outcome |
Report UI action outcome (telemetry) | POST /telemetry/action |
Local agent coordination (stored only on this machine):
| Tool | Title | Endpoint |
|---|---|---|
post_note |
Post a note to the agent noticeboard | POST /notes |
Reading deep UI trees (Chromium/Electron)
get_ui_tree defaults to depth=4, which is enough for native Win32 apps. Chromium/Electron
apps (VS Code, Slack, Discord, Claude Desktop, Teams) bury content under ~10 levels of
Pane/Group wrappers — at low depth the response is only empty panes. Ask for depth=15-20
there (max 30) and cap cost with max_nodes (default 200, max 1000): max_nodes is the cost
brake, not depth. When the response has truncated: true, the tree was cut — repeat with a
higher depth/max_nodes before concluding anything about the window.
Acting: two families, and picking the wrong one is the classic failure
This is the part agents get wrong by default, because every other computer-use tool they have ever seen needs the window in front. Here, most of them do not:
ui_act picks between the two families below for you — try it first for click / type / pick.
It attempts UI Automation and drops to real input by itself only when UIA reports the pattern is
missing on that element (never for intent=escolher, where a physical click would trigger the
element instead of picking an option inside it), and tells you which one ran in mecanismo
(uia/fisico). It also refuses an ambiguous target with 409 alvo_ambiguo and hands back the
candidates with their rect, instead of silently taking the first name match the way the tools
below do. Read on for what each family means and when to call one of them directly instead.
| Family | Tools | Needs the window in the foreground? |
|---|---|---|
| By element (UI Automation) | ui_invoke, ui_set_value, ui_select_option |
No. Works with the window behind others, unfocused, while the user keeps typing elsewhere. |
| By synthetic input | ui_send_keys, ui_drag |
Yes. Refuses with janela_nao_esta_em_primeiro_plano otherwise. |
Why: the first family talks to the app's accessibility provider and ignores z-order; the second
emits real keyboard/mouse events, which Windows delivers to whatever is in the foreground — not
to the hwnd you passed.
Calling the families directly: start with by-element, every time. Do not call focus_window
"just in case" before it: that steals the user's foreground and buys nothing. Reach for ui_send_keys only
after ui_set_value actually returned valor_nao_aplicado on that field (a contenteditable
in a controlled framework), and for ui_drag only for what genuinely only moves by dragging —
there is no UIA pattern for dragging.
If focus_window itself fails with foco_nao_aplicado, do not loop on the second family: it
cannot succeed without the foreground. health_check reports the real-input arm (ForgePilot)
under executor/forgepilot, and warns when it is installed but stopped.
Privacy
No data about you leaves the machine. There is no remote telemetry, no cloud service, and no account. There is exactly one outbound request, it carries nothing about you, and you can turn it off:
Update check. Once a day the engine asks GitHub's public Releases API whether a newer version exists. The request goes to GitHub, not to us: no identifier, no telemetry, nothing about your machine or your apps. It can be switched off in the tray menu, and when off no outbound request is made at all. Everything else in AIPM remains local.
Network
- The backend listens on the loopback interface only (
127.0.0.1:9147) — not on0.0.0.0, so nothing on the LAN can reach it. - Every request must carry a
Hostheader oflocalhostor127.0.0.1; anything else is rejected with403 forbidden_host(anti DNS-rebinding, so a web page you visit cannot drive the API). - This MCP server makes exactly one kind of outbound call: HTTP to that local address. It sends
a
User-Agentofmcp:<your MCP client name>so the local audit log shows which agent asked.
Read-only by default
- The 15 perception tools plus
ui_findare plain reads.ui_find_atis also semantically read-only, but its pixel probe uses a guardedPOST; all 17 carryreadOnlyHint: true. - The 7 UI action tools (
ui_act,ui_invoke,ui_set_value,ui_send_keys,ui_drag,ui_select_option,focus_window) return403 action_denieduntil the user does both: enable Agent actions in the tray menu and add the target process to a per-app allowlist. Neither is on by default, and the setting is per app — allowing Notepad does not allow the browser.
What the telemetry stores — metadata only
Recorded: app/process name, element role (Button, Edit…), the element name the agent
asked for, the action (invoke/set_value/focus), success or failure, duration in ms, and a
failure reason. Two mechanical invariants make "metadata only" verifiable rather than a promise:
- An action record stores what the agent requested, not what the app displayed. The role and
name come from the agent's own
role=/name_contains=arguments. The name of the element actually resolved on screen is never written, so what the tool saw never becomes telemetry. - The failure reason is a closed vocabulary (
elemento_nao_encontrado,ui_timeout,erro_uia,outro, …). Any other string is stored asoutro. An exception message — which could carry a file path or on-screen text — therefore cannot reach the disk.
Never stored: screen contents, window text read by read_window, the text typed by
ui_set_value (value=), file contents, keystrokes, screenshots. The passively learned UI shape
(ui_shape) holds only counts, UIA role names, depth and booleans: exposes_text says whether
text exists, named_controls says how many elements have a name — never the text itself.
Masking: before any request is recorded, value= and api_key= are replaced with ***, so
neither get_audit_log nor the on-disk query log can reveal typed text or a secret.
One honest nuance: the audit/query log stores the request line, so other query arguments
stay readable — e.g. check_file(path=D:/videos/out.mp4) is logged as that path, and
check_process(title_contains=...) keeps that fragment. It is a local log of what the agent
asked for. Only value= and api_key= are masked.
Where the data lives, and how to delete it
Everything is under %LOCALAPPDATA%\AIProcessManager\:
| Path | Contents |
|---|---|
db\*.jsonl, db\rollup.json |
telemetry: tasks, actions, queries, UI shapes, counters |
ledger.jsonl |
tamper-evident hash-chained log of reported/executed actions (metadata only) |
actions.cfg |
whether the action tier is on + the per-app allowlist |
update.json |
update-check preference (on/off) and its cache: last check time, latest tag, dismissed tag |
log.txt, endpoint.txt |
app log and the API address currently in use |
To erase: quit the app from the tray, then delete the folder (or just db\ to reset learning and
the economy counters; deleting actions.cfg turns the action tier back off). Nothing is written
anywhere else, and the /audit ring buffer lives in memory only — it disappears when the app
closes. You can inspect everything the store holds with get_audit_log, get_economy_stats, and
GET /analytics/actions.
Troubleshooting
| Symptom | Meaning | Fix |
|---|---|---|
connection_refused |
AIProcessManager.exe is not running | Start it from the Start menu (green tray icon) |
action_denied |
Action tier off, or app not in the allowlist | Tray menu → Agent actions, then allow that app |
api_paused |
The user paused the API from the tray | Tray menu → Resume API |
Empty Pane tree |
depth too low for a Chromium/Electron app |
Retry get_ui_tree with depth=17 |
Every error payload carries a next_action field with the same guidance.
Coverage (measured, honest)
| Stack | Read state | Semantic actions |
|---|---|---|
| Win32 / WinForms / WPF / UWP | ✅ full | ✅ |
| Delphi VCL (legacy business apps) | ✅ full | ✅ |
| Console (cmd, PowerShell, Windows Terminal) | ✅ text | — |
| Chromium / Electron (Chrome, Cursor, Claude Desktop) | ✅ after waking the a11y tree | ✅ |
| Electron on the legacy MSAA bridge (e.g. Discord) | ⚠️ wakes, but ~120 ms/node — too slow today | ⚠️ |
| Java Swing | ⚠️ needs the Java Access Bridge | roadmap |
We publish what does not work yet on purpose — you should know the edges before relying on it.
Behaviour note: the first read of a Chromium/Electron window asks it to activate its accessibility tree — the same standard request a screen reader makes. That app then keeps computing accessibility data (a CPU cost in that app) and does not go back to sleep on its own. Native Win32 apps are unaffected.
Free vs paid
- Free & open (MIT): this MCP server.
- Free (closed): the
AIProcessManager.exebackend — the sensor. Yours to run at no cost. - Paid: AIPM Pilot, the autonomous computer-use agent that drives apps end-to-end using AIPM's structured perception.
Support the project
If AIPM saves you tokens, consider sponsoring.
License
MIT for the MCP server. The backend and AIPM Pilot are separate products.
AI Process Manager MCP questions
How do I add AI Process Manager MCP to Claude Code?
Run claude mcp add aipm -- npx -y aipm-mcp-server in your terminal. Add --scope user to make it available in every project.
How do I add AI Process Manager MCP to Cursor?
Open ~/.cursor/mcp.json and add the server under mcpServers, using the Cursor config shown in the install section above.
What tools does AI Process Manager MCP provide?
It exposes 28 tools, including aipm_ja_faz, health_check, check_process, list_processes, list_windows.
Does this server use screenshots?
No, it uses structured JSON and text from processes, windows, and UI Automation trees, which is significantly more token-efficient than screenshots.
Is my data sent to the cloud?
No, all data remains local on your machine. There is no remote telemetry or cloud service, and the backend only listens on the local loopback interface.
Can the agent interact with windows that are not in the foreground?
Yes, tools using the UI Automation family can interact with windows even if they are behind other windows or unfocused.