Power your agent
คำสั่งของผู้เผยแพร่เอง ไม่ใช่เอนด์พอยต์ของ PlugMCP
Host a copy with our keys and logs.
uvx boyce==0.1.1Claude Code ไม่มีลิงก์ติดตั้งสำหรับคำสั่งแบบโลคัล ให้คัดลอกคำสั่งด้านล่างแล้วรันในเทอร์มินัล
BOYCE_DB_URL=<value> BOYCE_PROVIDER=<value> ANTHROPIC_API_KEY=<value> claude mcp add io.github.boyce-io-boyce -- uvx boyce==0.1.1รันในเทอร์มินัล
{ "mcpServers": { "io.github.boyce-io-boyce": { "command": "uvx", "args": [ "boyce==0.1.1" ], "env": { "BOYCE_DB_URL": "<value>", "BOYCE_PROVIDER": "<value>", "ANTHROPIC_API_KEY": "<value>" } } }}claude_desktop_config.json
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รันบน PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
เปิดจากผู้เผยแพร่
The semantic safety layer for agentic database workflows. Boyce connects LLMs to live database context with built-in safety rails.
Named for Raymond F. Boyce, co-inventor of SQL (1974) and co-author of Boyce-Codd Normal Form (BCNF).
Deterministic SQL compiler for AI agents. Your agent stops guessing SQL.
AI agents querying databases without proper context generate unreliable SQL — working from incomplete schemas, inferring column names, guessing join paths. Boyce gives agents the structured database intelligence they need to generate correct, safe SQL every time — through three interconnected systems:
Why does this matter? → The Null Trap: Your AI Agent's SQL Is Correct. The Answer Is Still Wrong.
Requires Python 3.10+
pip install boyce
# With live Postgres/Redshift adapter (enables EXPLAIN pre-flight + column profiling)
pip install "boyce[postgres]"
# uv (recommended)
uv pip install boyce
uv pip install "boyce[postgres]"
From source:
git clone https://github.com/boyce-io/boyce
uv pip install -e "boyce/"
After installing, run boyce init to configure your MCP host automatically:
boyce init
The wizard detects Claude Desktop, Cursor, Claude Code, and JetBrains (DataGrip, IntelliJ, etc.), and writes the correct config block for each.
Developing from source? The repo includes a setup script:
./quickstart.sh # detects uv or python, installs package, writes .env template
The fastest path is boyce init — it detects your MCP host and writes the config automatically:
boyce init
Or configure manually. There are two setup paths depending on your host:
If you're using Claude Desktop, Cursor, Claude Code, Codex, Cline, Windsurf, JetBrains (DataGrip,
IntelliJ), or any MCP-compatible host, you do not need to configure an LLM provider for Boyce.
The host's own model handles reasoning — Boyce supplies the schema context and deterministic SQL
compiler via get_schema and ask_boyce. Only BOYCE_DB_URL is needed (and even that is optional).
Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"boyce": {
"command": "boyce",
"env": {
"BOYCE_DB_URL": "postgresql://user:pass@host:5432/db"
}
}
}
}
Cursor (.cursor/mcp.json in project root):
{
"mcpServers": {
"boyce": {
"command": "boyce",
"env": {
"BOYCE_DB_URL": "postgresql://user:pass@host:5432/db"
}
}
}
}
If you're using the CLI (boyce ask), HTTP API, or a non-MCP client (e.g., the VS Code
extension), configure Boyce's internal query planner with your LLM provider:
{
"mcpServers": {
"boyce": {
"command": "boyce",
"env": {
"BOYCE_PROVIDER": "anthropic",
"BOYCE_MODEL": "claude-sonnet-4-6",
"ANTHROPIC_API_KEY": "sk-ant-...",
"BOYCE_DB_URL": "postgresql://user:pass@host:5432/db"
}
}
}
}
Boyce supports any LLM provider available through LiteLLM: Anthropic, OpenAI, Ollama (local), vLLM (local), Azure, Bedrock, Vertex, Mistral, and more.
BOYCE_DB_URL is optional on both paths. Without it, Boyce runs in schema-only mode — SQL
generation still works; EXPLAIN pre-flight and live query tools return "status": "unchecked".
SemanticSnapshot (JSON)
│
▼ ingest_source
┌─────────────────────────────────────────────┐
│ SemanticGraph (NetworkX) │ ← in-memory, loaded per session
│ nodes = entities (tables/views/dbt models) │
│ edges = joins (weighted by confidence) │
└─────────────────────────────────────────────┘
│ │
▼ ask_boyce ▼ (internal)
QueryPlanner Dijkstra
(LiteLLM) join resolver
NL → StructuredFilter │
│ │
└──────────┬────────────────┘
▼
kernel.process_request() ← ZERO LLM HERE
SQLBuilder (dialect-aware)
│
▼
EXPLAIN pre-flight ← Query Verification
(PostgresAdapter)
│
▼
SQL + validation result
Dialect support: redshift, postgres, duckdb, bigquery
Redshift safety rails (safety.py): Automatic linting for LATERAL, JSONB, REGEXP_COUNT, lookahead regex patterns, and numeric cast rewrites for Redshift 1.0 (PG 8.0.2).
# Scan a single file
boyce scan demo/magic_moment/manifest.json
# Scan a directory (auto-detects all parseable sources)
boyce scan ./my-project/ -v
# Save snapshots for MCP server use
boyce scan ./my-project/ --save
10 parsers: dbt manifest, dbt project, LookML, SQLite, DDL, CSV, Parquet, Django, SQLAlchemy, Prisma.
# Unit tests — no DB required, runs in ~4 seconds
python boyce/tests/verify_eyes.py
# Expected output:
# Ran 15 tests in 3.5s
# OK
# ✅ All checks passed.
The ingest_source tool accepts a SemanticSnapshot JSON dict. Minimal example:
{
"snapshot_id": "<sha256>",
"source_system": "dbt",
"entities": {
"entity:orders": {
"id": "entity:orders",
"name": "orders",
"schema": "public",
"fields": ["field:orders:order_id", "field:orders:revenue"]
}
},
"fields": {
"field:orders:order_id": {
"id": "field:orders:order_id",
"entity_id": "entity:orders",
"name": "order_id",
"field_type": "ID",
"data_type": "INTEGER"
}
},
"joins": []
}
See boyce/tests/live_fire/mock_snapshot.json for a complete field/entity example.
boyce/ ← PRIMARY — headless FastMCP server + pip package
├── boyce/
│ ├── server.py ← MCP entry point (8 tools)
│ ├── kernel.py ← Deterministic SQL kernel
│ ├── graph.py ← SemanticGraph (NetworkX)
│ ├── safety.py ← Redshift compatibility rails
│ ├── types.py ← Protocol contract (Pydantic)
│ ├── scan.py ← Scan CLI (boyce scan)
│ ├── connections.py ← DSN persistence (ConnectionStore)
│ ├── doctor.py ← Environment diagnostics (boyce doctor)
│ ├── sql/ ← SQLBuilder, dialect layer, join resolver
│ ├── parsers/ ← 10 parsers (dbt, lookml, ddl, sqlite, csv, etc.)
│ ├── planner/ ← QueryPlanner (LiteLLM → StructuredFilter)
│ └── adapters/ ← PostgresAdapter (Eyes)
└── tests/
├── verify_eyes.py ← 15-test suite, no DB required
├── test_parsers.py ← Parser tests (all 10 parsers)
├── test_scan.py ← Scan CLI tests
└── live_fire/ ← Docker Compose integration tests
Copyright 2026 Convergent Methods, LLC. MIT License.
Deterministic SQL compiler for AI agents. Your agent stops guessing SQL.
{ "mcpServers": { "io.github.boyce-io-boyce": { "command": "uvx", "args": [ "boyce==0.1.1" ], "env": { "BOYCE_DB_URL": "<value>", "BOYCE_PROVIDER": "<value>", "ANTHROPIC_API_KEY": "<value>" } } }}เครื่องมือ
ยังไม่มีรายการเครื่องมือ เซิร์ฟเวอร์แบบรีโมตจะได้รายการหลังการตรวจสอบสถานะครั้งแรก
FAQ
คัดลอกคอนฟิก stdio สำหรับ Cursor, Claude Desktop, Claude Code หรือ VS Code ได้ในหน้านี้ คอนฟิกนี้ใช้การติดตั้งของผู้เผยแพร่ ไม่ใช่พร็อกซีของ PlugMCP
ผู้เผยแพร่ระบุตัวแปรสภาพแวดล้อมเหล่านี้: BOYCE_DB_URL, BOYCE_PROVIDER, ANTHROPIC_API_KEY
Boyce ทำงานแบบโลคัลผ่าน stdio
ตรวจสอบล่าสุดเมื่อ 2026-11-09 Deterministic SQL compiler for AI agents. Your agent stops guessing SQL.