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gaussdbdocs-mcp-server

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gaussdbdocs-mcp-server

Local MCP server for GaussDB documentation semantic search + read-only metadata access. Apache-2.0 · Python 3.12 · Qdrant 1.12 · MCP 1.x

English · 中文

English

What is this?

A Model-Context-Protocol server that gives Claude Desktop / Cursor (and any other MCP client) two capabilities against a GaussDB instance:

  1. Hybrid semantic search over the GaussDB documentation corpus — dense (BGE-large-zh-v1.5) + sparse (BM25) + Reciprocal Rank Fusion (k=60). Built for the database's high identifier density (GUC / WAL / XID / TOAST etc.).

  2. Read-only introspection of a live GaussDB instance — metadata tools (list_databases, list_schemas, list_tables, etc.) and EXPLAIN for query plans. DML/DDL/DCL are rejected at the Python layer BEFORE any SQL leaves the process.

One-command install

git clone https://github.com/songmenglin-dev/gaussdbdocs-mcp-server.git
cd gaussdbdocs-mcp-server
./setup.sh            # or: ./setup.sh v1   # pin a snapshot
docker compose ps     # confirm qdrant + mcp-server both healthy

setup.sh validates Docker availability, copies .env.example → .env, downloads the index-v*.tar.gz snapshot from GitHub Releases into the named index_data volume, and brings up the stack. Target: ≤ 10 minutes on a clean Linux box.

Architecture

.chm → parse_chm → chunk → BGE + BM25 → Qdrant (named vectors: dense + sparse)
                                  ↓
                       export snapshot → GitHub Releases (BUILD)
                                  ↓
                  setup.sh downloads index-v*.tar.gz (RUN)
                                  ↓
                       import_snapshot → Qdrant storage
                                  ↓
              MCP server (stdio / SSE) — hybrid retrieval + DB tools

MCP tools (11 total)

Tool

Requires

Description

query_gaussdb_docs(query, top_k)

—

Hybrid retrieval

search_sql_reference(query, edition?, top_k)

—

SQL syntax lookup (filtered to doc_type=sql_reference)

search_admin_guide(query, edition?, top_k)

—

Operational guidance lookup

compare_gaussdb_editions(topic, top_k_per_side)

—

Paired evidence across distributed / centralized

list_databases

GAUSSDB_DSN

Enumerate databases the role can see

list_schemas(schema?)

GAUSSDB_DSN

Schemas (default: all)

list_tables(schema?)

GAUSSDB_DSN

Tables (default: user schemas)

list_indexes(table)

GAUSSDB_DSN

Indexes on a table

describe_table(table)

GAUSSDB_DSN

Columns + types + nullability + defaults

show_performance_views

GAUSSDB_DSN

pg_stat_* performance views

explain_query(sql)

GAUSSDB_DSN

EXPLAIN only — EXPLAIN ANALYZE is rejected

The DB tools are only registered when GAUSSDB_DSN is configured; without it, the docs surface (4 tools) is the entire tool list.

Configuration

All config via env vars (see .env.example):

QDRANT_HOST=qdrant               # service hostname
QDRANT_PORT=6333
QDRANT_GRPC_PORT=6334
INDEX_ARCHIVE=/data/index.tar.gz
EMBEDDING_MODEL=BAAI/bge-large-zh-v1.5
BM25_MODEL=Qdrant/bm25
RETRIEVAL_MODE=hybrid           # hybrid | dense | sparse
RRF_K=60
MCP_TRANSPORT=stdio             # stdio | sse
MCP_SSE_PORT=8080
GAUSSDB_DSN=postgresql://user:pass@host:5432/db  # optional
LOG_LEVEL=INFO

Development

make test-unit     # fast unit tests
make test          # full suite (in-memory Qdrant)
make lint          # ruff
make build-index   # run the BUILD pipeline
make docker-build  # production image

Project status

Batch

What

Status

1

Scaffold + config + logging

✅

2

CHM parse + chunk

✅

3

Embedding + Qdrant index + snapshot export

✅

4

Snapshot import + hybrid RRF + keyword_critical regression + domain tools

✅

5

MCP server (stdio + SSE)

✅

6

GaussDB read-only connector + DB tools

✅

7

Docker / Compose / setup.sh / CI / Release

🚧

8

Eval harness

⏳

9

Coverage gate + community files

⏳

License

Apache-2.0 — see LICENSE.

Related MCP server: ragi

中文

这是什么？

一个 Model-Context-Protocol (MCP) 服务器，给 Claude Desktop / Cursor（以及任何兼容 MCP 的客户端）提供两个能力对接 GaussDB：

  1. GaussDB 文档语料库的混合语义检索 — dense（BGE-large-zh-v1.5） + sparse（BM25） + Reciprocal Rank Fusion（k=60）。专为数据库文档的高专有名词密度（GUC / WAL / XID / TOAST 等）调优。

  2. 活 GaussDB 实例的只读内省 — 元数据工具（list_databases、list_schemas、list_tables 等）和 EXPLAIN 看查询计划。DML/DDL/DCL 在 Python 层 SQL 离开进程前 就被拒绝。

一键安装

git clone https://github.com/songmenglin-dev/gaussdbdocs-mcp-server.git
cd gaussdbdocs-mcp-server
./setup.sh             # 或 ./setup.sh v1 钉特定版本
docker compose ps      # 确认 qdrant + mcp-server 都 healthy

setup.sh 校验 Docker 可用性、把 .env.example 拷成 .env、从 GitHub Releases 下载 index-v*.tar.gz 到命名卷 index_data、然后启动整套栈。目标：干净 Linux 机器 ≤ 10 分钟上线。

架构

.chm → parse_chm → chunk → BGE + BM25 → Qdrant（named vectors: dense + sparse）
                                  ↓
                  export snapshot → GitHub Releases（BUILD）
                                  ↓
            setup.sh 下载 index-v*.tar.gz（RUN）
                                  ↓
                 import_snapshot → Qdrant storage
                                  ↓
           MCP server（stdio / SSE）— 混合检索 + DB 工具

开发

make test-unit   # 快速单元测试
make test        # 全套（in-memory Qdrant）
make lint        # ruff
make build-index # 跑 BUILD pipeline
make docker-build

许可证

Apache-2.0 — 见 LICENSE。

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