Factsets
БесплатноНе проверенA self-maintaining knowledge base for AI agents that manages facts, resources, skills, and execution logs via MCP, enabling persistent context and tag-based org
Описание
A self-maintaining knowledge base for AI agents that manages facts, resources, skills, and execution logs via MCP, enabling persistent context and tag-based organization.
README
| Package | |
| CI/CD | Release Tests codecov |
A self-maintaining knowledge base for AI agents, exposed via the Model Context Protocol (MCP). Manages facts (atomic knowledge), resources (cached external content), skills (procedural markdown), and execution logs (command history) using SQLite.
Features
- Persistent Context - Knowledge survives across sessions
- Self-Maintaining - Staleness detection with refresh instructions
- Tag-Based Organization - Flexible categorization and retrieval
- Skill Documents - Markdown files for procedural knowledge
- User Preferences - Configurable output style and agent behavior
- MCP Protocol - Standard interface for AI tool/prompt definitions
Installation
npm install --global factsets
pnpm install --global factsets
bun install --global factsets
Quick Start
As MCP Server
Add to your MCP client configuration (Claude Desktop, GitHub Copilot, Cursor, etc.), using bunx, npx or pnpm dlx accordingly:
{
"mcpServers": {
"factsets": {
"command": "bunx",
"args": ["factsets", "mcp-server"]
}
}
}
Or run directly:
bunx factsets mcp-server
First-Time Setup
After adding Factsets to your MCP client, run the setup prompt to integrate it into your project:
In a supported IDE: Type /mcp.factsets.setup in the chat to run the guided setup
In other clients: Call the get_setup_guide tool or use the setup prompt
The setup guide will:
- Analyze your project structure and establish baseline facts
- Configure the skills directory for your AI client
- Create or update
AGENTS.mdwith Factsets instructions - Migrate any existing skills with Factsets integration
- Register key configuration files as resources
This one-time setup ensures agents have full context on every future interaction.
CLI Commands
# Start MCP server (default command - auto-watches skill files and seeds starter content)
bunx factsets [--database-url <path>] [--client <type>]
# Explicit mcp-server command (same as above)
bunx factsets mcp-server [--database-url <path>] [--client <type>]
# Start without file watching
bunx factsets --no-watch-skills
# Start without seeding starter content
bunx factsets --no-seed
# Run file watcher standalone
bunx factsets watch-files [--database-url <path>]
# Run background maintenance worker
bunx factsets worker [--database-url <path>]
# Export database to JSON
bunx factsets dump backup.json
# Restore database from JSON
bunx factsets restore backup.json
The --client flag configures where skill files are stored (e.g., github-copilot -> .github/prompts/skills/). If you want to change clients / your skill directory, do so through your agent which will migrate skills for you.
See Configuration Guide for all options.
Core Concepts
| Concept | Description |
|---|---|
| Facts | Atomic knowledge units (1-3 sentences), tagged and timestamped |
| Resources | External content (files, URLs, APIs) with cached snapshots and retrieval methods |
| Skills | Markdown documents for procedural knowledge, stored on filesystem |
| Execution Logs | Command history with success/failure tracking for skill validation |
| Tags | Flexible categorization for all content types |
MCP Tools
Facts
| Tool | Description |
|---|---|
submit_facts |
Add facts with tags and source tracking |
search_facts |
Query facts by tags, content, or filters |
verify_facts |
Mark facts as verified by ID |
verify_facts_by_tags |
Bulk verify facts by tags |
update_fact |
Update fact content, metadata, or tags |
delete_facts |
Remove facts by criteria |
restore_facts |
Restore soft-deleted facts |
Resources
| Tool | Description |
|---|---|
add_resources |
Register resources with retrieval methods |
search_resources |
Find resources by tags, type, or URI |
get_resources |
Get resources by ID or URI with freshness |
update_resource_snapshot |
Update cached content for single resource |
update_resource_snapshots |
Bulk update cached content |
update_resource |
Update resource metadata (not content) |
delete_resources |
Remove resources |
restore_resources |
Restore soft-deleted resources |
Skills
| Tool | Description |
|---|---|
create_skill |
Create markdown skill document |
update_skill |
Update skill metadata/references |
search_skills |
Find skills by tags or query |
get_skills |
Get skills by name with content |
link_skill |
Link skill to facts/resources/skills |
sync_skill |
Sync skill after file edit |
delete_skills |
Remove skills |
get_dependency_graph |
Get skill dependency tree |
restore_skills |
Restore soft-deleted skills |
Execution Logs
| Tool | Description |
|---|---|
submit_execution_logs |
Record command/test/build executions |
search_execution_logs |
Find executions by query, tags, success |
get_execution_log |
Get execution details by ID |
Tags
| Tool | Description |
|---|---|
create_tags |
Create organizational tags |
list_tags |
List tags with usage counts |
update_tags |
Update tag descriptions |
prune_orphan_tags |
Clean up unused orphan tags |
Configuration
| Tool | Description |
|---|---|
get_config |
Get a configuration value by key |
set_config |
Set a configuration value |
delete_config |
Delete a configuration value |
list_config |
List all configuration with schema |
get_config_schema |
Get available options with descriptions |
User Preferences
| Tool | Description |
|---|---|
get_preference_prompt |
Get natural language preference prompt |
get_user_preferences |
Get structured preference data |
infer_preference |
Update preference from user behavior |
reset_preferences |
Reset preferences to defaults |
Maintenance
| Tool | Description |
|---|---|
check_stale |
Find stale resources and dependencies |
mark_resources_refreshed |
Mark resources as current |
Context & Guides
| Tool | Description |
|---|---|
get_knowledge_context |
Build context from tags (facts/resources/skills) |
build_skill_context |
Get skill with formatted content and refs |
get_maintenance_report |
Generate staleness/maintenance report |
get_refresh_guide |
Get instructions for refreshing a resource |
get_agent_guide |
Get the agent workflow guide (call first) |
get_concept_guide |
Get conceptual overview and design philosophy |
get_config_guide |
Get configuration guide with all options |
MCP Prompts
| Prompt | Description |
|---|---|
setup |
Guided setup for new project integration |
user_preferences |
Get user preferences for output formatting |
knowledge_context |
Build context from tags |
recall_skill |
Get skill with references |
maintenance_report |
Staleness summary |
refresh_guide |
Instructions to refresh a resource |
agent_guide |
Agent workflow guide (call first) |
concept |
Conceptual overview and philosophy |
config |
Configuration guide with all options |
Documentation
- Configuration Guide - CLI flags, client setup, and skills directory
- Design Reference - Full API documentation
- Concept - Philosophy and design rationale
- Agent Workflow - How agents use Factsets
Development
# Run tests
bun test
# Run full e2e (tests + build + dry run)
bun e2e
# Build distribution
bun dist
# Format code
bun format
# Lint
bun lint
# Generate database migrations
bun migrations
# Inspect MCP server with inspector
bun inspect
Установка Factsets
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/joshua-auchincloss/factsetsFAQ
Factsets MCP бесплатный?
Да, Factsets MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Factsets?
Нет, Factsets работает без API-ключей и переменных окружения.
Factsets — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Factsets в Claude Desktop, Claude Code или Cursor?
Открой Factsets на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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