PAPI: Persistent Adaptive Planning Intelligence vs Openclaw MCP
A side-by-side look at the PAPI: Persistent Adaptive Planning Intelligence and Openclaw MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose PAPI: Persistent Adaptive Planning Intelligence for coding agents work over a hosted endpoint; choose Openclaw MCP for coding agents as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose PAPI: Persistent Adaptive Planning Intelligence when
- You need dedicated capabilities in the Coding Agents domain.
- You prefer a remote HTTP/SSE transport.
- You want tools like
orient, setup, plan.
Choose Openclaw MCP when
- You need dedicated capabilities in the Coding Agents domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
OPENCLAW_URL, OPENCLAW_GATEWAY_TOKEN, OPENCLAW_AGENT_ID, OPENCLAW_MODEL, OPENCLAW_TIMEOUT_MS, AUTH_ENABLED, MCP_CLIENT_ID, MCP_CLIENT_SECRET. - You want tools like
openclaw_chat, openclaw_status, openclaw_chat_async.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Coding Agents | Coding Agents |
| Quality signal | 57/100 · Good | 68/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Remote HTTP/SSE | Local subprocess (stdio) |
| Auth | Not declared | API key required |
| Pricing | Not declared | Free |
| Required env vars | None listed | OPENCLAW_URLOPENCLAW_GATEWAY_TOKENOPENCLAW_AGENT_IDOPENCLAW_MODELOPENCLAW_TIMEOUT_MSAUTH_ENABLEDMCP_CLIENT_IDMCP_CLIENT_SECRET |
| Verified owner | Community listing | Community listing |
| GitHub stars | 11 | 188 |
| Directory activity | 1 views 0 installs 0 upvotes | 8 views 0 installs 0 upvotes |
| Tools | 15 | 7 |
| Full listing | View PAPI: Persistent Adaptive Planning Intelligence | View Openclaw MCP |
Tools & capabilities
PAPI: Persistent Adaptive Planning Intelligence tools 15
orientone call returns the current cycle, what's in flight, and the recommended next action. Run it at the start of every session.setupscaffold PAPI onto a new project.planbreak goals into a cycle of right-sized tasks, each with a build handoff your assistant can execute directly.build_listlist the current cycle's tasks and their handoffs.build_executestart a task (creates a branch and handoff) and complete it (records the build report).tutorial_modeturn on short explanations and one clear next step in every reply. Handy for your first few cycles.board_viewread the project board and any task.board_editchange a task's status, cycle, priority, or notes.ad_hocrecord quick work done outside the cycle so it shows in project history.ideacapture a feature, bug, or research note into the backlog.bugfile a bug against the board.strategy_reviewstep back every few cycles to check direction, not just velocity.- +3 more on the listing page
Openclaw MCP tools 7
openclaw_chatSend a message to OpenClaw and get a responseopenclaw_statusGet OpenClaw gateway status and health informationopenclaw_chat_asyncSend a message to OpenClaw asynchronously. Returns a task_id immediately that can be polled for results. Use this for potentially long-running conversations.openclaw_task_statusCheck the status of an async task. Returns status, and result if completed.openclaw_task_listList all tasks. Optionally filter by status, session, or instance.openclaw_task_cancelCancel a pending task. Only works for tasks that haven't started yet.openclaw_instancesList all configured OpenClaw instances. Shows instance names, URLs, and which is the default. Use instance names in other tools to target a specific OpenClaw gateway.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
PAPI: Persistent Adaptive Planning Intelligence
{
"mcpServers": {
"papi-persistent-adaptive-planning-intelligence": {
"url": "https://mcp.getpapi.ai/mcp"
}
}
}
Openclaw MCP
{
"mcpServers": {
"freema-openclaw-mcp": {
"command": "npx",
"args": [
"-y",
"openclaw-mcp"
],
"env": {
"OPENCLAW_URL": "YOUR_OPENCLAW_URL_HERE",
"OPENCLAW_GATEWAY_TOKEN": "YOUR_OPENCLAW_GATEWAY_TOKEN_HERE",
"OPENCLAW_AGENT_ID": "YOUR_OPENCLAW_AGENT_ID_HERE",
"OPENCLAW_MODEL": "YOUR_OPENCLAW_MODEL_HERE",
"OPENCLAW_TIMEOUT_MS": "YOUR_OPENCLAW_TIMEOUT_MS_HERE",
"AUTH_ENABLED": "YOUR_AUTH_ENABLED_HERE",
"MCP_CLIENT_ID": "YOUR_MCP_CLIENT_ID_HERE",
"MCP_CLIENT_SECRET": "YOUR_MCP_CLIENT_SECRET_HERE"
}
}
}
}
Frequently asked questions
PAPI: Persistent Adaptive Planning Intelligence is categorized under Coding Agents and uses a remote HTTP/SSE transport. Openclaw MCP belongs to Coding Agents and uses a local stdio subprocess. Pick PAPI: Persistent Adaptive Planning Intelligence for coding agents work and Openclaw MCP for coding agents.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
PAPI: Persistent Adaptive Planning Intelligence has no declared pricing — check the project's own site. Openclaw MCP is listed as free. Auth: api key required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add papi-persistent-adaptive-planning-intelligence and freema-openclaw-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, PAPI: Persistent Adaptive Planning Intelligence has a quality signal of 57/100 (Good) with 1 views, 0 installs and 11 GitHub stars. Openclaw MCP has 68/100 (Great) with 8 views, 0 installs and 188 GitHub stars.