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PAPI: Persistent Adaptive Project Intelligence

NPM · @PAPI-AI/SERVER · 2 COMPONENTS · SCANNED SEP 20

Adaptive plan/build/review cycles for AI coding assistants, persisted across sessions.

+2 this week 77 Trust /100
Trust breakdown (7 categories)

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →

Supply Chain Security88
  • No malware found by supply-chain analysis.Pass
  • CVE check failed: a known medium-severity CVE affects @anthropic-ai/sdk 0.82.0, a direct dependency. A fixed version is available. View diagnostics → Fail
  • No install/post-install scripts declared.Pass
  • 33 of 105 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency35
  • Source repository is publicly reachable at the declared URL. View diagnostics → Pass
  • Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
  • License check failed: the license (Elastic-2.0) isn't a recognized OSI-approved license. See how to fix → Fail
  • Actively maintained (last published 4 days ago).Pass
  • Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability63
  • AI-judged instruction clarity (excellent).Pass
  • Context-footprint check failed: tool/resource definitions use about 18191 tokens (~324/item across 56 items; 56 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management100
  • No destabilizing schema changes in the last 30 days.Pass
Tool Coverage100
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 100% of tool parameters carry a description.Pass
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • All 5 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation.Pass
  • An AI judge read all 56 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
  • Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Install

How do I install the PAPI: Persistent Adaptive Project Intelligence MCP server?

PAPI: Persistent Adaptive Project Intelligence runs locally as an npm package, launched with npx -y @papi-ai/server. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

npm · @papi-ai/server

# add to Claude Code
claude mcp add getpapi-papi -- npx -y @papi-ai/server
// .cursor/mcp.json
{
  "mcpServers": {
    "getpapi-papi": {
      "command": "npx",
      "args": [
        "-y",
        "@papi-ai/server"
      ]
    }
  }
}
// .vscode/mcp.json
{
  "servers": {
    "getpapi-papi": {
      "command": "npx",
      "args": [
        "-y",
        "@papi-ai/server"
      ]
    }
  }
}
# add to Codex CLI
codex mcp add getpapi-papi -- npx -y @papi-ai/server
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "getpapi-papi": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "@papi-ai/server"
      ],
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add getpapi-papi --command npx --arg -y --arg @papi-ai/server
# ~/.hermes/config.yaml
mcp_servers:
  getpapi-papi:
    command: "npx"
    args: ["-y", "@papi-ai/server"]
// ~/.netclaw/config/netclaw.json
{
  "McpServers": {
    "getpapi-papi": {
      "Transport": "stdio",
      "Command": "npx",
      "Arguments": [
        "-y",
        "@papi-ai/server"
      ]
    }
  }
}
# add to Vellum
assistant mcp add getpapi-papi -t stdio -c npx -a -y @papi-ai/server
// mcp.json
{
  "mcpServers": {
    "getpapi-papi": {
      "command": "npx",
      "args": [
        "-y",
        "@papi-ai/server"
      ]
    }
  }
}
Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 20 Sept 26 +1
    • Stability: 0.97 → pass security
  • 19 Sept 26 −1
    • Stability: pass → 0.97 functional
  • 18 Sept 26 +1
    • Stability: 0.97 → pass security
  • 17 Sept 26 −1
    • Stability: pass → 0.97 functional
  • 16 Sept 26 +1
    • Stability: 0.97 → pass security
  • 14 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 90 to 93. That category is still filling its 30-day observation window: 27 days of observed history at the previous scan, 28 at this one. The score rises as the window fills, whether or not the server changes.

  • 12 Sept 26 −2
    • Stability: pass → 0.87 functional
  • 10 Sept 26 +1
    • Stability: 0.97 → pass security
Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 20 Sept 2026 · Analysed npm/@papi-ai/server@0.7.85

Provenance No attestation

The registry publishes no build provenance for this version, so there is nothing to verify.

Result No attestation
Ecosystem npm

Background: How many MCP packages publish verified provenance →

Vulnerabilities 1 finding
ID CVE Severity Vector Fix available
GHSA-p7fg-763f-g4gf CVE-2026-41686 medium yes

Background: What a vulnerability scan can and cannot prove →

Dependencies 105 packages
Packages resolved 105
Stale 33
Tree resolution Complete

Background: SBOMs and build attestations, explained →

MCP tools · 56 exposed · ~18,191 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens
setup ~864

Give a project a memory, so every later session starts with its context instead of a blank slate. Setup reads the project, writes a Product Brief that says what it is for and who it serves, records the first Active Decisions and build conventions so settled answers outlive the session that found them, and installs the workflow instructions the coding assistant follows from then on. Everything after this (planning, building, reviewing) reads from what setup writes. It takes a few minutes and runs in two passes: the first returns prompts for you to execute, the second saves the results. Tell the user what each pass is doing while it runs. Run after configuring your MCP credentials (via `init` or manually from getpapi.ai). Only project_name is required — description and target_users are derived from README, package.json, and commit history when omitted. Set existing_project: true to adopt an existing codebase. ADOPTING AN EXISTING PROJECT OVER A REMOTE/HOSTED CONNECTOR (no local stdio install): PAPI cannot read your filesystem, so YOU (the client) must gather a `codebase_scan` and pass it in — list top-level dirs/files, the package manifest, the README (first ~3000 chars), and recent commit subjects. Without it, adoption falls back to asking for description/target_users. On a local stdio install PAPI scans the tree itself, so `codebase_scan` is optional there. First call returns prompts (prepare phase), then call again with mode "apply" and your outputs. After setup, run `plan` to start your first cycle.

NameTypeReqDescription
ad_seed_responsestringYour generated AD seed JSON array (mode "apply" only). Optional.
brief_responsestringYour generated Product Brief markdown (mode "apply" only).
codebase_scanobjectClient-gathered scan of the user's codebase for existing_project adoption. REQUIRED for adoption over a remote/hosted connector (PAPI cannot read your filesystem there); optional on a local stdio ins…
constraintsstringTechnical or business constraints (e.g. "must use PostgreSQL", "HIPAA compliant").
conventions_responsestringYour generated conventions markdown to append to CLAUDE.md (mode "apply" only). Optional.
deployment_targetstringDeployment environment. Optional — defaults to "cloud".
descriptionstringWhat the project does — one or two sentences. Optional: PAPI will derive this from README, package.json, and recent commit history when omitted.
existing_projectbooleanSet to true when adopting an existing codebase. PAPI will scan the project structure and generate context-aware setup artifacts.
forcebooleanSet to true to overwrite an existing Product Brief. Defaults to false.
initial_tasks_responsestringYour generated initial tasks JSON array (mode "apply" only, existing_project only).
modestring"prepare" returns prompts for brief/AD/convention generation. "apply" accepts your outputs. Defaults to "prepare" when omitted.
north_star_responsestringThe project's North Star statement — one or two sentences (mode "apply" only). Provide the statement you extracted from the docs or agreed with the user in response to the prepare-phase North Star pr…
problemsstringKey problems it solves. Optional — PAPI will infer from description if omitted.
project_namestringyesName of the project.
project_typestringProject archetype. Optional — defaults to "other", PAPI recommends based on description.
sourcesstringComma-separated local file paths to reference docs (briefs, specs, READMEs) that provide additional project context. Only used with existing_project: true.
target_usersstringWho is this for? Role and context. Optional: PAPI will derive this from README and project context when omitted.
team_sizestringTeam size. Optional — defaults to "solo".

No output schema declared.

No examples provided.

strategy_agenda ~192

Queue topics for the next strategy review. Topics surface as input in the next `strategy_review` prepare phase and are automatically marked as addressed after the review completes. Two modes: "add" to queue a topic, "list" to see pending topics. Use this when you spot a strategic question during a build — capture the topic now instead of losing it.

NameTypeReqDescription
modestring"add" to queue a topic (requires `topic`). "list" returns all pending topics. Defaults to "list" when omitted.
sourcestringOptional origin label — e.g. "manual", "carry-forward", "idea". Defaults to "manual".
source_cyclenumberOptional cycle number this topic originated from (mode "add" only).
topicstringThe topic to queue (mode "add" only). One sentence describing what the next strategy review should consider.

No output schema declared.

No examples provided.

strategy_change ~448

Apply a strategic shift to the project. Three modes: "capture" for lightweight mid-conversation decision capture (no LLM round-trip), "prepare" to get a change prompt for full analysis, "apply" to persist analysis output. Use "capture" when you detect a strategic decision in conversation and want to persist it quickly without disrupting the build flow. In "capture" mode, pass north_star to directly set/update the project North Star (no decision text needed).

NameTypeReqDescription
ad_bodystringFull AD body in markdown format including ### heading (mode "capture" only). If omitted, a body is auto-generated from the text field.
ad_idstringExisting AD ID to update (mode "capture" only). Omit to create a new AD.
confidencestringConfidence level for the AD (mode "capture" only). Defaults to MEDIUM.
confidence_onlybooleanWhen true (mode "capture" + ad_id required), only update the confidence level — leave the AD body unchanged. Use when evidence strength changes but the decision itself hasn't shifted.
cycle_numbernumberThe cycle number from prepare phase (mode "apply" only).
llm_responsestringYour raw output from executing the change prompt (mode "apply" only).
modestring"capture" for lightweight direct persistence (no LLM needed). "prepare" returns the change prompt. "apply" accepts your output. Defaults to "prepare" when omitted.
north_starstringmode "capture" only — set/update the project North Star statement directly. orient and the project foundation read it. No decision text required when this is provided.
supersedesstringExisting AD ID this new decision replaces, e.g. "AD-42" (mode "capture" only). The named AD is marked superseded and kept as history — never overwritten. Use this instead of passing ad_id when the de…
textstringDescription of the strategic shift to apply (e.g. "Pivot from B2C to enterprise B2B").

No output schema declared.

No examples provided.

strategy_review ~419

Run a Strategy Review — assesses project direction, velocity, and Active Decisions. Produces recommendations and potential AD updates that feed into the next plan. Offered every 5 cycles; hard-blocked at 7+ overdue cycles. Run it in your current conversation — only start a fresh one if you are genuinely under context pressure (your host just compacted, you are near the context limit, or the session is heavy with build context), not just because a review is next. First call returns a review prompt for you to execute (prepare phase). Then call again with mode "apply" and your output. Pass `force: true` to run before the cadence gate.

NameTypeReqDescription
cycle_numbernumberThe cycle number from prepare phase (mode "apply" only).
dispatchstring"inline" (default) returns the review prompt for the calling LLM to execute directly. "subagent" returns a Task() invocation prompt to dispatch the heavyweight reasoning to a fresh sub-agent. The app…
forcebooleanBypass the 5-cycle cadence gate and run an early review. Use when you need a strategy review before the regular cadence — e.g. after a major pivot, unexpected blockers, or when recent builds have sig…
llm_responsestringYour raw output from executing the review prompt (mode "apply" only).
llm_response_filestringAbsolute path to a file containing the review output (mode "apply" only). LOCAL stdio servers only — on the hosted connection the server cannot read files on your machine; pass llm_response inline in…
modestring"prepare" returns the review prompt. "apply" accepts your output. Defaults to "prepare" when omitted.

No output schema declared.

No examples provided.

task_claim ~113

Claim a task from the shared org Pool into your personal backlog (assignee = you). Atomic first-claim-wins — a concurrent double-claim is impossible. Cascades the DEPENDS ON chain: claiming a task also claims its not-Done prerequisites; if any prerequisite is already claimed by another member the whole claim is refused (a build unit is never split across owners). Does not call the Anthropic API.

NameTypeReqDescription
task_idstringyesThe task to claim, e.g. "task-2071".

No output schema declared.

No examples provided.

task_move ~186

Move a task from the current project to another project you own. Reassigns the task a fresh id in the target (collision-free) and carries its build reports, comments, and history with it; the cycle assignment is cleared so it lands in the target project's backlog. You must own (or have write access to) BOTH projects. Destructive-ish and cross-project, so it requires confirm=true — without it you get a preview only. Does not call the Anthropic API.

NameTypeReqDescription
confirmbooleanSet true to perform the move. Omit (or false) to get a preview of what would happen.
target_projectstringyesThe destination project — its slug (e.g. "papi-ui") or UUID. Must be a project you own.
task_idstringyesThe task to move, e.g. "task-2292".

No output schema declared.

No examples provided.

task_unclaim ~84

Release a task you claimed back to the shared Pool (clears assignee). Claimer-only and pre-review — you cannot unclaim another member's task or one that has reached In Review/Done. Does not cascade. Does not call the Anthropic API.

NameTypeReqDescription
task_idstringyesThe task to unclaim, e.g. "task-2071".

No output schema declared.

No examples provided.

zoom_out ~311

Run a Zoom-Out Retrospective — a higher-level meta-retrospective that sits above strategy reviews. Analyses the full project arc: every cycle, decision, and pivot. Use when you want to step back and see the big picture after many cycles. First call returns a prompt (prepare phase). Then call again with mode "apply" and your output.

NameTypeReqDescription
cycle_numbernumberThe cycle number from prepare phase (mode "apply" only).
dispatchstring"inline" (default) returns the retrospective prompt for the calling LLM to execute directly. "subagent" returns a Task() invocation prompt to dispatch the heavyweight reasoning to a fresh sub-agent.…
llm_responsestringYour raw output from executing the retrospective prompt (mode "apply" only).
llm_response_filestringAbsolute path to a file containing the zoom-out output (mode "apply" only). LOCAL stdio servers only — on the hosted connection the server cannot read files on your machine. Use when the response is…
modestring"prepare" returns the retrospective prompt. "apply" accepts your output. Defaults to "prepare" when omitted.

No output schema declared.

No examples provided.

Common questions

What is the PAPI: Persistent Adaptive Project Intelligence MCP server?

PAPI: Persistent Adaptive Project Intelligence is an MCP server listed in the public MCP registry as io.github.getpapi/papi. Adaptive plan/build/review cycles for AI coding assistants, persisted across sessions. This page covers its npm package (@papi-ai/server).

Is the PAPI: Persistent Adaptive Project Intelligence MCP server safe to use?

PAPI: Persistent Adaptive Project Intelligence scores 77 out of 100 on VerifyMCP. We recorded 1 known advisory against it as of 20 September 2026. It declares no install or post-install scripts. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

What tools does the PAPI: Persistent Adaptive Project Intelligence MCP server expose?

PAPI: Persistent Adaptive Project Intelligence exposes 56 tools: plan, strategy_review, strategy_change, strategy_agenda, board_view, and 51 more. Their descriptions and schemas cost roughly 18,191 tokens of context every time the server is loaded.

Is the PAPI: Persistent Adaptive Project Intelligence MCP server still maintained?

PAPI: Persistent Adaptive Project Intelligence is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

What licence is the PAPI: Persistent Adaptive Project Intelligence MCP server under?

PAPI: Persistent Adaptive Project Intelligence declares the Elastic-2.0 licence, which is not on the OSI-approved list. Read the terms before using it at work, and note this covers the source only, not the cost of any service it calls.