Crawler Summary

agentrem answer-first brief

Structured reminders CLI for AI agents with MCP server ๐Ÿ”” agentrem $1 $1 $1 $1 $1 Structured reminders for AI agents. Persistent, searchable, works across sessions. Instant Start --- For AI Agents Copy this into your CLAUDE.md / AGENTS.md (or run agentrem setup to generate it): --- MCP Server For Claude Desktop and any MCP client โ€” add to ~/Library/Application Support/Claude/claude_desktop_config.json: No global install? Use npx: Run agentrem setup --mcp to print this co Capability contract not published. No trust telemetry is available yet. 1 GitHub stars reported by the source. Last updated 2/25/2026.

Freshness

Last checked 2/25/2026

Best For

agentrem is best for reminders, ai-agent, cli workflows where MCP compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB MCP, runtime-metrics, public facts pack

Claim this agent
Agent DossierGitHubSafety: 89/100

agentrem

Structured reminders CLI for AI agents with MCP server ๐Ÿ”” agentrem $1 $1 $1 $1 $1 Structured reminders for AI agents. Persistent, searchable, works across sessions. Instant Start --- For AI Agents Copy this into your CLAUDE.md / AGENTS.md (or run agentrem setup to generate it): --- MCP Server For Claude Desktop and any MCP client โ€” add to ~/Library/Application Support/Claude/claude_desktop_config.json: No global install? Use npx: Run agentrem setup --mcp to print this co

MCPself-declared

Public facts

4

Change events

0

Artifacts

0

Freshness

Feb 25, 2026

Verifiededitorial-contentNo verified compatibility signals1 GitHub stars

Capability contract not published. No trust telemetry is available yet. 1 GitHub stars reported by the source. Last updated 2/25/2026.

1 GitHub starsTrust evidence available

Trust score

Unknown

Compatibility

MCP

Freshness

Feb 25, 2026

Vendor

Github

Artifacts

0

Benchmarks

0

Last release

1.11.0

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. 1 GitHub stars reported by the source. Last updated 2/25/2026.

Setup snapshot

git clone https://github.com/fraction12/agentrem.git
  1. 1

    Setup complexity is MEDIUM. Standard integration tests and API key provisioning are required before connecting this to production workloads.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Github

profilemedium
Observed Feb 25, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

MCP

contractmedium
Observed Feb 25, 2026Source linkProvenance
Adoption (1)

Adoption signal

1 GitHub stars

profilemedium
Observed Feb 25, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB MCP

Extracted files

0

Examples

6

Snippets

0

Languages

typescript

Executable Examples

bash

npx agentrem add "Deploy to prod" --due tomorrow --priority 2
npx agentrem check
npx agentrem list

markdown

## Reminders
You have access to `agentrem` CLI for persistent reminders across sessions.

### On every session start, run:
agentrem check --type time,session --budget 800

### When the user says "remind me", "don't forget", "follow up", or "next time":
agentrem add "<content>" --due "<when>" --priority <1-5> --tags "<tags>"

### Key commands:
- `agentrem add` โ€” create a reminder
- `agentrem check` โ€” see what's triggered/due
- `agentrem check --watch` โ€” block until next reminder fires
- `agentrem list` โ€” list all active reminders
- `agentrem search <query>` โ€” full-text search
- `agentrem complete <id>` โ€” mark done
- `agentrem snooze <id> --for 2h` โ€” snooze
- `agentrem --help` โ€” full reference

json

{
  "mcpServers": {
    "agentrem": {
      "command": "agentrem-mcp",
      "args": []
    }
  }
}

json

{
  "mcpServers": {
    "agentrem": {
      "command": "npx",
      "args": ["-y", "agentrem", "mcp"]
    }
  }
}

bash

--due "now"                   # Immediately
--due "today"                 # Today at 23:59
--due "tomorrow"              # Tomorrow at 09:00
--due "in 5 minutes"
--due "in 2 hours"
--due "in 3 days"
--due "in 1 week"
--due "+5m"                   # Short relative
--due "+2h"
--due "+3d"
--due "+1w"
--due "2026-04-01T09:00:00"   # ISO datetime
--due "2026-04-01"            # ISO date

bash

# Wait indefinitely for next reminder
agentrem check --watch

# Exit 1 if nothing fires within 5 minutes
agentrem check --watch --timeout 300

# Get the full reminder as JSON when it fires
agentrem check --watch --json

# Filter by trigger type and agent
agentrem check --watch --type time,heartbeat --agent jarvis --timeout 60

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB MCP

Docs source

GITHUB MCP

Editorial quality

ready

Structured reminders CLI for AI agents with MCP server ๐Ÿ”” agentrem $1 $1 $1 $1 $1 Structured reminders for AI agents. Persistent, searchable, works across sessions. Instant Start --- For AI Agents Copy this into your CLAUDE.md / AGENTS.md (or run agentrem setup to generate it): --- MCP Server For Claude Desktop and any MCP client โ€” add to ~/Library/Application Support/Claude/claude_desktop_config.json: No global install? Use npx: Run agentrem setup --mcp to print this co

Full README

๐Ÿ”” agentrem

npm version CI License: MIT Node.js MCP

Structured reminders for AI agents. Persistent, searchable, works across sessions.

Instant Start

npx agentrem add "Deploy to prod" --due tomorrow --priority 2
npx agentrem check
npx agentrem list

For AI Agents

Copy this into your CLAUDE.md / AGENTS.md (or run agentrem setup to generate it):

## Reminders
You have access to `agentrem` CLI for persistent reminders across sessions.

### On every session start, run:
agentrem check --type time,session --budget 800

### When the user says "remind me", "don't forget", "follow up", or "next time":
agentrem add "<content>" --due "<when>" --priority <1-5> --tags "<tags>"

### Key commands:
- `agentrem add` โ€” create a reminder
- `agentrem check` โ€” see what's triggered/due
- `agentrem check --watch` โ€” block until next reminder fires
- `agentrem list` โ€” list all active reminders
- `agentrem search <query>` โ€” full-text search
- `agentrem complete <id>` โ€” mark done
- `agentrem snooze <id> --for 2h` โ€” snooze
- `agentrem --help` โ€” full reference

MCP Server

For Claude Desktop and any MCP client โ€” add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "agentrem": {
      "command": "agentrem-mcp",
      "args": []
    }
  }
}

No global install? Use npx:

{
  "mcpServers": {
    "agentrem": {
      "command": "npx",
      "args": ["-y", "agentrem", "mcp"]
    }
  }
}

Run agentrem setup --mcp to print this config. MCP tools: add_reminder ยท check_reminders ยท list_reminders ยท search_reminders ยท complete_reminder ยท snooze_reminder ยท edit_reminder ยท delete_reminder ยท get_stats ยท get_history ยท undo_change ยท garbage_collect ยท export_reminders ยท import_reminders


All Commands

| Command | Key Flags | Example | |---------|-----------|---------| | add <content> | --due --priority --tags --trigger --recur --agent --context --category --depends-on --dry-run | agentrem add "PR review" --due "+4h" --priority 2 | | check | --type --text --budget --format --json --escalate --agent --dry-run | agentrem check --type time,session --budget 800 --json | | check --watch | --timeout --json --type --agent | agentrem check --watch --timeout 300 --json | | list | --status --priority --tag --due --limit --json --all --agent --category --trigger --format | agentrem list --priority 1,2 --json | | search <query> | --status --limit --json | agentrem search "deploy staging" --json | | complete <id> | --notes | agentrem complete abc12345 | | snooze <id> | --until --for | agentrem snooze abc12345 --for 2h | | edit <id> | --content --due --priority --tags --add-tags --remove-tags --context --category --agent | agentrem edit abc12345 --priority 1 | | delete [id] | --permanent --status --older-than | agentrem delete abc12345 --permanent | | stats | --json | agentrem stats --json | | history [id] | --limit --json | agentrem history --limit 20 --json | | undo <history_id> | โ€” | agentrem undo 42 | | gc | --older-than --dry-run | agentrem gc --older-than 30 | | export | --out --status | agentrem export --out backup.json | | import <file> | --merge --replace --dry-run | agentrem import backup.json --merge | | watch | --interval --once --verbose --on-fire --on-fire-preset --on-fire-timeout --install --uninstall --status --agent | agentrem watch --on-fire-preset openclaw | | setup | --mcp | agentrem setup / agentrem setup --mcp | | doctor | --json | agentrem doctor | | init | --force | agentrem init | | quickstart | โ€” | agentrem quickstart | | schema | โ€” | agentrem schema |

--json is available on check, list, search, stats, history, doctor โ€” use it for structured output in your agent.

Trigger Types

| Type | Fires when... | Key flags | |------|--------------|-----------| | time | Due datetime is reached | --due (notifies once by default; stays active until explicitly completed) | | keyword | Message text matches | --keywords, --match any\|all\|regex | | condition | Shell command output matches | --check, --expect | | session | Every session start check | โ€” | | heartbeat | Every heartbeat check | โ€” | | manual | Explicit check only | โ€” |

Priority Levels

| Level | Label | Behavior | |-------|-------|----------| | 1 | ๐Ÿ”ด Critical | Always surfaced | | 2 | ๐ŸŸก High | Surfaced within 60% budget | | 3 | ๐Ÿ”ต Normal | Surfaced within 85% budget | | 4 | โšช Low | Counted but not surfaced | | 5 | ๐Ÿ’ค Someday | Skipped entirely |


Natural Language Dates

--due, --until, and --decay all accept natural language:

--due "now"                   # Immediately
--due "today"                 # Today at 23:59
--due "tomorrow"              # Tomorrow at 09:00
--due "in 5 minutes"
--due "in 2 hours"
--due "in 3 days"
--due "in 1 week"
--due "+5m"                   # Short relative
--due "+2h"
--due "+3d"
--due "+1w"
--due "2026-04-01T09:00:00"   # ISO datetime
--due "2026-04-01"            # ISO date

check --watch: Blocking Mode

agentrem check --watch blocks until the next due reminder fires. Useful for scripting, pipelines, or pausing an agent until something needs attention.

# Wait indefinitely for next reminder
agentrem check --watch

# Exit 1 if nothing fires within 5 minutes
agentrem check --watch --timeout 300

# Get the full reminder as JSON when it fires
agentrem check --watch --json

# Filter by trigger type and agent
agentrem check --watch --type time,heartbeat --agent jarvis --timeout 60

Exit codes: 0 = reminder found (or SIGINT/SIGTERM), 1 = timeout elapsed with no reminder.

Note: --watch does not update fire counts. Use a regular agentrem check after to actually mark reminders as fired.

Poll-then-act pattern:

if agentrem check --watch --timeout 120 --json > /tmp/due.json; then
  echo "Reminder fired:"
  cat /tmp/due.json
  agentrem check   # mark as fired
fi

watch --on-fire: Hooks

โš ๏ธ Security: The --on-fire command runs with your user's permissions. Only use trusted commands. Reminder data is passed via environment variables (never shell-interpolated) to prevent injection.

Execute a shell command whenever a reminder fires:

agentrem watch --on-fire "curl -X POST https://hooks.example.com/reminder"

Reminder data is passed as environment variables (no shell injection โ€” data never interpolated into the command):

| Variable | Description | |----------|-------------| | AGENTREM_ID | Reminder ID | | AGENTREM_CONTENT | Reminder text | | AGENTREM_PRIORITY | Priority (1-5) | | AGENTREM_TAGS | Comma-separated tags | | AGENTREM_CONTEXT | Context string | | AGENTREM_DUE | Due datetime | | AGENTREM_FIRE_COUNT | Number of times fired |

  • Fire-and-forget โ€” failures are logged to ~/.agentrem/logs/on-fire.log, never crash the watcher
  • Sequential โ€” multiple reminders process one at a time
  • Timeout: 5 seconds default, configurable with --on-fire-timeout <ms>

Built-in presets โ€” skip the shell command entirely:

agentrem watch --on-fire-preset openclaw   # auto-delivers to your OpenClaw agent

Or craft your own:

agentrem watch --on-fire 'curl -X POST https://hooks.example.com/reminder -d "text=$AGENTREM_CONTENT"'

Background Watcher

agentrem watch polls for due reminders and fires native OS notifications.

agentrem watch                           # Poll every 30s (foreground)
agentrem watch --interval 60             # Custom interval
agentrem watch --once                    # Single check and exit
agentrem watch --agent jarvis            # Watch for a specific agent
agentrem watch --verbose                 # Show poll log

# Install as OS service (auto-start on boot)
agentrem watch --install
agentrem watch --install --interval 60
agentrem watch --status
agentrem watch --uninstall

Service files: macOS โ†’ ~/Library/LaunchAgents/com.agentrem.watch.plist ยท Linux โ†’ ~/.config/systemd/user/agentrem-watch.service ยท Logs โ†’ ~/.agentrem/logs/watch.log


Native Notifications ๐Ÿ””

On macOS, agentrem ships a bundled Swift app (Agentrem.app) that runs as a singleton process โ€” notifications appear under "agentrem" with a bell icon.

| Priority | Sound | |----------|-------| | P1 ๐Ÿ”ด Critical | Hero | | P2 ๐ŸŸก High | Ping | | P3 ๐Ÿ”ต Normal | Pop |

Notification behavior:

  • Click body โ†’ notification re-appears (won't dismiss until you act on it)
  • Complete โœ… โ†’ marks reminder complete and dismisses (the only way to complete a fired reminder)
  • Multiple reminders โ†’ single process handles all via IPC
  • Fallback chain: Agentrem.app โ†’ terminal-notifier โ†’ osascript โ†’ console

To rebuild the Swift app: npm run build:notify


Programmatic API

Use agentrem directly from JavaScript/TypeScript โ€” no CLI subprocess needed.

npm install agentrem
import { add, check, list, complete, snooze, search, stats } from 'agentrem';
import type { Reminder } from 'agentrem';

// Add a reminder
const rem = await add('Review PR #42', { due: 'tomorrow', priority: 2, tags: 'pr,review' });

// Check for triggered reminders (session start pattern)
const { included, totalTriggered } = await check({ type: 'time,session', budget: 800 });
for (const r of included) {
  console.log(`[P${r.priority}] ${r.content}`);
}

// List active reminders
const reminders = await list({ limit: 20 });

// Complete a reminder
const done = await complete(rem.id, 'Reviewed and merged');

// Snooze a reminder
const snoozed = await snooze(rem.id, { for: '2h' });

// Full-text search
const results = await search('deploy staging');

// Get statistics
const s = await stats();
console.log(`${s.totalActive} active, ${s.overdue} overdue`);

All API functions are async and return full Reminder objects. The database is auto-initialized on first call (no manual init needed).

See llms-full.txt for complete type signatures and all options.


Why agentrem?

# vs flat files / memory.md
agentrem check --json   # structured output your agent can parse; memory.md can't do that
  • Persistent across sessions โ€” SQLite-backed, survives restarts, not just in-context notes
  • Priority-aware + token budgets โ€” check --budget 800 fits within any context window without overflow
  • Triggerable โ€” time, keyword, condition, session, heartbeat triggers; not just static lists
  • Blocking watch mode โ€” check --watch lets agents pause until something needs attention
  • Agent-native โ€” --json everywhere, --agent namespacing, MCP server for chat clients

Install

npm install -g agentrem

The database auto-initializes on first use. Run agentrem setup to get your CLAUDE.md snippet, or agentrem setup --mcp for Claude Desktop.

MIT License

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB MCP

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

MCP: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://xpersona.co/api/v1/agents/mcp-fraction12-agentrem/snapshot"
curl -s "https://xpersona.co/api/v1/agents/mcp-fraction12-agentrem/contract"
curl -s "https://xpersona.co/api/v1/agents/mcp-fraction12-agentrem/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors
GITLAB_AI_CATALOGgitlab-mcp

Rank

83

A Model Context Protocol (MCP) server for GitLab

Traction

No public download signal

Freshness

Updated 2d ago

MCP
GITLAB_PUBLIC_PROJECTSgitlab-mcp

Rank

80

A Model Context Protocol (MCP) server for GitLab

Traction

No public download signal

Freshness

Updated 2d ago

MCP
GITLAB_AI_CATALOGrmcp-openapi

Rank

74

Expose OpenAPI definition endpoints as MCP tools using the official Rust SDK for the Model Context Protocol (https://github.com/modelcontextprotocol/rust-sdk)

Traction

No public download signal

Freshness

Updated 2d ago

MCP
GITLAB_AI_CATALOGrmcp-actix-web

Rank

72

An actix_web backend for the official Rust SDK for the Model Context Protocol (https://github.com/modelcontextprotocol/rust-sdk)

Traction

No public download signal

Freshness

Updated 2d ago

MCP
Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://xpersona.co/api/v1/agents/mcp-fraction12-agentrem/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/mcp-fraction12-agentrem/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/mcp-fraction12-agentrem/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/mcp-fraction12-agentrem/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/mcp-fraction12-agentrem/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/mcp-fraction12-agentrem/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "MCP"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_MCP",
      "generatedAt": "2026-04-17T02:13:04.809Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "MCP",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "reminders",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "ai-agent",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "cli",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "mcp",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "mcp-server",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "sqlite",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "llm",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "llm-tools",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "ai-tools",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "agent-tools",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "agent-memory",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "persistent-memory",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "model-context-protocol",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "claude",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "claude-code",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "claude-desktop",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "cursor",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "windsurf",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "openai",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "anthropic",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "coding-agent",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    },
    {
      "key": "vibe-coding",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:MCP|unknown|profile capability:reminders|supported|profile capability:ai-agent|supported|profile capability:cli|supported|profile capability:mcp|supported|profile capability:mcp-server|supported|profile capability:sqlite|supported|profile capability:llm|supported|profile capability:llm-tools|supported|profile capability:ai-tools|supported|profile capability:agent-tools|supported|profile capability:agent-memory|supported|profile capability:persistent-memory|supported|profile capability:model-context-protocol|supported|profile capability:claude|supported|profile capability:claude-code|supported|profile capability:claude-desktop|supported|profile capability:cursor|supported|profile capability:windsurf|supported|profile capability:openai|supported|profile capability:anthropic|supported|profile capability:coding-agent|supported|profile capability:vibe-coding|supported|profile"
}

Facts JSON

[
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Github",
    "href": "https://fraction12.github.io/agentrem",
    "sourceUrl": "https://fraction12.github.io/agentrem",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-02-25T03:12:40.864Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "MCP",
    "href": "https://xpersona.co/api/v1/agents/mcp-fraction12-agentrem/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/mcp-fraction12-agentrem/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-02-25T03:12:40.864Z",
    "isPublic": true
  },
  {
    "factKey": "traction",
    "category": "adoption",
    "label": "Adoption signal",
    "value": "1 GitHub stars",
    "href": "https://github.com/fraction12/agentrem",
    "sourceUrl": "https://github.com/fraction12/agentrem",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-02-25T03:12:40.864Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://xpersona.co/api/v1/agents/mcp-fraction12-agentrem/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/mcp-fraction12-agentrem/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[]

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