Skip to content
verify mcp Beta VerifyMCP is currently in beta. If you notice any issues, get in touch and we’ll put it right.

io.github.Goldentrii/agent-recall

NPM · AGENT-RECALL-MCP · SCANNED SEP 24

Correction-first agent memory. Precision KPI tracks if agents heed warnings. 5 layers, local-only.

Available components

0 this week 79 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 Security98
  • No malware found by supply-chain analysis.Pass
  • No known CVEs affecting this package version or its production dependencies.Pass
  • No install/post-install scripts declared.Pass
  • 65 of 207 dependencies flagged as unhealthy (2 deprecated). View diagnostics → Partial
Provenance & Transparency19
Schema Quality & AI Usability81
  • 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
  • AI-judged instruction clarity (good).Pass
  • Context-footprint check failed: tool/resource definitions use about 916 tokens (~130/item across 7 items; 5 tools + 2 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 Coverage94
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 83% of tool parameters carry a description.Partial
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • We read all 5 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 6 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 io.github.Goldentrii/agent-recall MCP server?

io.github.Goldentrii/agent-recall runs locally as an npm package, launched with npx -y agent-recall-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

npm · agent-recall-mcp

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

  • 24 Sept 26 0
    • Stability: 0.97 → pass security
  • 23 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.

  • 21 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.

  • 19 Sept 26 −2
    • Stability: pass → 0.83 functional
  • 18 Sept 26 0
    • Stability: 0.97 → pass security
  • 17 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.

  • 15 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.

  • 12 Sept 26 −2
    • Stability: pass → 0.80 functional
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 24 Sept 2026 · Analysed npm/agent-recall-mcp@3.4.31

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 →

Dependencies 207 packages
Packages resolved 207
Deprecated 2
Stale 64
Tree resolution Complete

Background: SBOMs and build attestations, explained →

MCP tools · 5 exposed · ~872 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
check ~268

Use when the user asks to validate understanding, verify alignment, or check if their interpretation matches the human's intent.

NameTypeReqDescription
assumptionsarray–Key assumptions you're making.
confidencestring–How confident you are. Defaults to medium.
decision_idstring–Link multiple check calls to the same decision. Auto-generated if not provided.
deltastring–The gap between your understanding and reality (or 'none').
evidencearray–Evidence collected since prior. Each entry shifts probability.
goalstring–The goal or decision question you're checking alignment on. Required for alignment checks; optional when recording a pure decision trail (prior/posterior/evidence).
human_correctionstring–After human responds: what they actually wanted (or 'confirmed').
outcomestring–Final decision result: 'confirmed', 'rejected', 'partial', or free text. Triggers decision trail persistence.
posteriornumber–Updated probability after considering evidence (0-1).
priornumber–Initial probability estimate (0-1). Start of Bayesian decision trail.
projectstring––
understandingstring–Alias for goal — use when saying 'check my understanding: X'. Provide either goal or understanding.

No output schema declared.

No examples provided.

recall ~126

Use when the user asks to recall, search, find, or look up previous memory, context, or decisions.

NameTypeReqDescription
feedbackarray–Rate previous recall results to improve future ranking. Pass {id, useful:true} for each result you actually used; {id, useful:false} for noise.
limitinteger–Max results after RRF merge.
projectstring––
querystringyesWhat to search for.
sincestring–ISO date ("2026-05-01") or relative duration ("7d"). Filters journal results.

No output schema declared.

No examples provided.

remember ~124

Use when the user asks to remember, store, note, or save a specific decision, fact, or insight.

NameTypeReqDescription
contentstringyesWhat to remember.
contextstring–Routing hint. Values: 'architecture' or 'decision' → palace/architecture room. 'blocker' or 'blocked' → palace/blockers room. 'goal' → palace/goals room. 'lesson' or 'insight' → awareness. 'qa' or 'c…
projectstring––

No output schema declared.

No examples provided.

session_end ~223

Use when the user asks to save, checkpoint, summarize, end, retain, or persist the current session. Optionally pass close_phase / open_phase to update the project pipeline narrative spine in the same call.

NameTypeReqDescription
close_phaseobject–Close the currently active pipeline phase as part of this save. Provide all three reflection fields explicitly — never auto-generated.
insightsarray–Insights learned this session.
open_phaseobject–Open a new pipeline phase as part of this save (e.g. when a watershed session pivots into the next strategic direction).
projectstring––
summarystringyesWhat happened this session. Simple session: 2-3 sentences. Multi-phase session: one paragraph per completed phase (e.g. 'Phase 1 — Name: what happened. Phase 2 — Name: what happened. Decisions: X. Bl…
trajectorystring–Where is the work heading next.

No output schema declared.

No examples provided.

session_start ~131

Use when the user asks to start, load, continue, resume, or open memory for a project. Set mode='lite' for a ≤500-token briefing (good for fresh conversations where the agent will pull memory on demand via recall/memory_query/skill_recall).

NameTypeReqDescription
contextstring–Optional context for matching cross-project insights
modestring–'lite' = ≤500-token sketch; agent must pull on demand. 'full' = current rich payload.
projectstring––
verboseboolean–Set true to get full JSON context instead of terse summary

No output schema declared.

No examples provided.

Common questions

What is the io.github.Goldentrii/agent-recall MCP server?

io.github.Goldentrii/agent-recall is an MCP server listed in the public MCP registry as io.github.Goldentrii/agent-recall. Correction-first agent memory. Precision KPI tracks if agents heed warnings. 5 layers, local-only. This page covers its npm package (agent-recall-mcp).

Is the io.github.Goldentrii/agent-recall MCP server safe to use?

io.github.Goldentrii/agent-recall scores 79 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 24 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 io.github.Goldentrii/agent-recall MCP server expose?

io.github.Goldentrii/agent-recall exposes 5 tools: session_start, session_end, remember, recall, check. Their descriptions and schemas cost roughly 872 tokens of context every time the server is loaded.

Is the io.github.Goldentrii/agent-recall MCP server still maintained?

io.github.Goldentrii/agent-recall is still listed as active in the MCP registry. We last reached this channel on 24 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 io.github.Goldentrii/agent-recall MCP server under?

io.github.Goldentrii/agent-recall declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.