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The following commit(s) were added to refs/heads/master by this push:
new 6d3c128 0.5.1 Version (#28)
6d3c128 is described below
commit 6d3c128f54437a5cbf01f1f2bf76b4e91de40e26
Author: Yijia Su <[email protected]>
AuthorDate: Tue Jul 15 11:56:46 2025 +0800
0.5.1 Version (#28)
0.5.1 Version (#28)
---
.env.example | 2 +-
README.md | 9 +++++++--
pyproject.toml | 2 +-
3 files changed, 9 insertions(+), 4 deletions(-)
diff --git a/.env.example b/.env.example
index 4f00c1a..167c2f7 100644
--- a/.env.example
+++ b/.env.example
@@ -133,7 +133,7 @@ ALERT_WEBHOOK_URL=
# Basic server information
SERVER_NAME=doris-mcp-server
-SERVER_VERSION=0.5.0
+SERVER_VERSION=0.5.1
SERVER_PORT=3000
# Temporary files directory
diff --git a/README.md b/README.md
index 6432ee7..3ba73ae 100644
--- a/README.md
+++ b/README.md
@@ -21,7 +21,7 @@ under the License.
Doris MCP (Model Context Protocol) Server is a backend service built with
Python and FastAPI. It implements the MCP, allowing clients to interact with it
through defined "Tools". It's primarily designed to connect to Apache Doris
databases, potentially leveraging Large Language Models (LLMs) for tasks like
converting natural language queries to SQL (NL2SQL), executing queries, and
performing metadata management and analysis.
-## 🚀 What's New in v0.5.0
+## 🚀 What's New in v0.5.1
- **🔥 Critical at_eof Connection Fix**: **Complete elimination of at_eof
connection pool errors** through redesigned connection pool strategy with zero
minimum connections, intelligent health monitoring, automatic retry mechanisms,
and self-healing pool recovery - achieving 99.9% connection stability
improvement
- **🔧 Revolutionary Logging System**: **Enterprise-grade logging overhaul**
with level-based file separation (debug, info, warning, error, critical),
automatic cleanup scheduler with 30-day retention, millisecond precision
timestamps, dedicated audit trails, and zero-maintenance log management
@@ -32,8 +32,13 @@ Doris MCP (Model Context Protocol) Server is a backend
service built with Python
- **⚙️ Enhanced Configuration Management**: Complete ADBC configuration system
with environment variable support, dynamic tool registration, and intelligent
parameter validation
- **🔒 Security & Compatibility Improvements**: Resolved pandas JSON
serialization issues, enhanced enterprise security integration, and maintained
full backward compatibility with v0.4.x versions
- **🎯 Modular Architecture**: 6 new specialized tool modules for enterprise
analytics with comprehensive English documentation and robust error handling
+- **🕒 Global SQL Timeout Configuration Enhancement**: Unified global SQL
timeout control via `config/performance/query_timeout`. All SQL executions now
use this value by default, with runtime override supported. This ensures
consistent timeout behavior across all entry points (MCP tools, API, batch
queries, etc.).
+- **Bug Fixes for Timeout Application**: Fixed issues where some SQL
executions did not correctly apply the global timeout configuration. Now, all
SQL executions are consistently controlled by the global timeout setting.
+- **Improved Robustness**: Optimized the timeout propagation chain in core
classes like `QueryRequest` and `DorisQueryExecutor`, preventing timeout
failures due to missing parameters.
+- **Documentation & Configuration Updates**: Updated documentation and
configuration instructions to clarify the priority and scope of the timeout
configuration.
+- **Other Bug Fixes & Optimizations**: Various known bug fixes and detail
optimizations for improved stability and reliability.
-> **🚀 Major Milestone**: This release establishes v0.5.0 as a
**production-ready enterprise data governance platform** with **critical
stability improvements** (complete at_eof fix + intelligent logging), 23 total
tools (14 existing + 7 analytics + 2 ADBC tools), and enterprise-grade system
reliability - representing a major advancement in both data intelligence
capabilities and operational stability.
+> **🚀 Major Milestone**: This release establishes v0.5.1 as a
**production-ready enterprise data governance platform** with **critical
stability improvements** (complete at_eof fix + intelligent logging + unified
SQL timeout), 25 total tools (15 existing + 8 analytics + 2 ADBC tools), and
enterprise-grade system reliability - representing a major advancement in both
data intelligence capabilities and operational stability.
## Core Features
diff --git a/pyproject.toml b/pyproject.toml
index 0902c3d..4623341 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -20,7 +20,7 @@ build-backend = "hatchling.build"
[project]
name = "doris-mcp-server"
-version = "0.5.0"
+version = "0.5.1"
description = "Enterprise-grade Model Context Protocol (MCP) server
implementation for Apache Doris"
authors = [
{name = "Yijia Su", email = "[email protected]"}
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