release-intel
release-intel-mcp
一个从 GitHub 仓库数据生成发布情报的 MCP 服务器。它关联任意两个 git ref 之间的提交、拉取请求、问题与贡献者,并返回结构化上下文,供 AI 综合生成发布说明、变更日志和发布摘要。
工具
get_changes_between_refs
获取两个 git ref 之间的所有提交,并附带相关的 PR 元数据、作者信息和关联问题。
字段 | 类型 | 描述 |
| string | GitHub 仓库所有者或组织 |
| string | GitHub 仓库名称 |
| string | 基础 ref(较早的标签、分支或 SHA) |
| string | 目标 ref(较新的标签、分支或 SHA) |
get_pull_requests_in_range
获取两个 ref 之间所有已合并的 PR,并按标签自动分类为:breaking、feature、fix、docs、chore、dependencies、other。
输入字段与 get_changes_between_refs 相同。
get_release_summary
生成一个结构化的发布上下文对象,包含提交数据、PR 元数据、关联问题、贡献者列表和汇总统计。
字段 | 类型 | 描述 |
| string | GitHub 仓库所有者 |
| string | GitHub 仓库名称 |
| string | 上一个发布标签(基础) |
| string | 新的发布标签或 HEAD |
Related MCP server: MCP Releases Server
设置
所有选项都需要具有 repo 读取权限的 GitHub 个人访问令牌。
在此处生成:https://github.com/settings/tokens
选项 A:stdio(本地进程)
标准方式:MCP 客户端将服务器作为本地子进程启动。
Claude Desktop
配置文件:~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"release-intel": {
"command": "npx",
"args": ["-y", "@barissozudogru/release-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}Claude Code
claude mcp add release-intel -e GITHUB_TOKEN=ghp_your_token -- npx -y @barissozudogru/release-intel-mcpCursor
配置文件:~/.cursor/mcp.json
{
"mcpServers": {
"release-intel": {
"command": "npx",
"args": ["-y", "@barissozudogru/release-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}Windsurf
配置文件:~/.codeium/windsurf/mcp_config.json
{
"mcpServers": {
"release-intel": {
"command": "npx",
"args": ["-y", "@barissozudogru/release-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}VS Code + Copilot
配置文件:.vscode/mcp.json
{
"servers": {
"release-intel": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@barissozudogru/release-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}Cline
配置文件:~/.cline/mcp_settings.json(或通过 Cline 扩展设置界面)
{
"mcpServers": {
"release-intel": {
"command": "npx",
"args": ["-y", "@barissozudogru/release-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}Continue.dev
配置文件:~/.continue/config.yaml
mcpServers:
- name: release-intel
command: npx
args:
- -y
- "@barissozudogru/release-intel-mcp"
env:
GITHUB_TOKEN: ghp_your_tokenZed
配置文件:~/.config/zed/settings.json
{
"context_servers": {
"release-intel": {
"command": {
"path": "npx",
"args": ["-y", "@barissozudogru/release-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}
}JetBrains (AI Assistant plugin)
{
"mcpServers": {
"release-intel": {
"command": "npx",
"args": ["-y", "@barissozudogru/release-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}选项 B:HTTP(远程 / 无状态)
将服务器作为 HTTP 端点运行。适用于远程客户端、团队共享部署,或偏好基于 URL 连接的客户端。
GITHUB_TOKEN=ghp_your_token npx @barissozudogru/release-intel-mcp --http默认在 3000 端口启动。设置 PORT 可更改端口。
Cursor (HTTP)
{
"mcpServers": {
"release-intel": {
"url": "http://localhost:3000/mcp"
}
}
}VS Code + Copilot (HTTP)
{
"servers": {
"release-intel": {
"type": "http",
"url": "http://localhost:3000/mcp"
}
}
}Windsurf (HTTP)
{
"mcpServers": {
"release-intel": {
"serverUrl": "http://localhost:3000/mcp"
}
}
}Continue.dev (HTTP)
mcpServers:
- name: release-intel
type: streamable-http
url: http://localhost:3000/mcp健康检查端点位于 GET /health。
选项 C:Docker
docker build -t release-intel-mcp .
docker run -p 3000:3000 -e GITHUB_TOKEN=ghp_your_token release-intel-mcp容器默认以 HTTP 模式启动。MCP 端点为 http://localhost:3000/mcp。
环境变量
变量 | 必需 | 默认值 | 描述 |
| 是 | - | GitHub 个人访问令牌(repo 范围) |
| 否 | stdio | 设置为 |
| 否 | 3000 | HTTP 端口(仅 HTTP 模式) |
本地开发
git clone https://github.com/barissozudogru/release-intel-mcp.git
cd release-intel-mcp
npm install
npm run build
GITHUB_TOKEN=ghp_... node dist/index.js许可证
MIT
Available Tools
3 toolsget_changes_between_refsGet Changes Between RefsB
Get all commits between two git refs enriched with associated PR metadata, author information, and linked issues. Uses the GitHub compare API.
| Name | Required | Description | Default |
|---|---|---|---|
| base | Yes | Base ref (tag, branch, or commit SHA), the older point | |
| head | Yes | Head ref (tag, branch, or commit SHA), the newer point | |
| repo | Yes | GitHub repository name | |
| owner | Yes | GitHub repository owner (user or organization) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full burden of behavioral disclosure. It only says the tool 'gets' commits and uses the GitHub compare API; it does not mention pagination, rate limits, auth requirements, potential response size, or any other operational behavior beyond the implied read-only nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences with the main operation front-loaded and no filler. The mention of the GitHub compare API is brief and serves as useful context without bloating the definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with four required and fully documented parameters, the description plus schema covers the core invocation. It also states what the response contains semantically. However, with no output schema and no annotations, it leaves response shape, pagination, and error/limit behavior unspecified, so it is not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline applies. The schema already documents owner, repo, base, and head, including that base is the older point and head is the newer point. The description's phrase 'between two git refs' adds little semantic value beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action: get all commits between two git refs, and specifies the enrichment (PR metadata, author information, linked issues). It does not explicitly contrast with sibling tools like get_pull_requests_in_range or get_release_summary, but the commit-focused wording makes the distinction mostly clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance about when to use this tool versus the sibling tools. It names the GitHub compare API but does not explain when an agent should prefer this over get_pull_requests_in_range or get_release_summary, nor does it state prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_pull_requests_in_rangeGet Pull Requests in RangeA
Get all merged pull requests between two refs with full metadata including labels, linked issues, review counts, and files changed. PRs are categorized by label into: breaking, feature, fix, docs, chore, dependencies, other.
| Name | Required | Description | Default |
|---|---|---|---|
| base | Yes | Base ref (tag, branch, or commit SHA), the older point | |
| head | Yes | Head ref (tag, branch, or commit SHA), the newer point | |
| repo | Yes | GitHub repository name | |
| owner | Yes | GitHub repository owner (user or organization) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It specifies that only merged PRs are returned, lists included metadata (labels, linked issues, review counts, files changed), and explains label categorization. It does not mention auth, pagination, or error behavior, but for a retrieval tool the core behavior is transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no filler. The key action and scope are front-loaded, and the category list adds useful detail without bloating the text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a straightforward read/list tool with all parameters documented in the schema, the description adequately covers what the tool returns and how results are categorized. It does not describe return format or pagination, but it is sufficiently complete for an agent to call it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents all four parameters. The description adds no parameter-specific details beyond what the schema provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific verb 'Get' and the precise resource ('all merged pull requests between two refs'). It differentiates from the siblings by emphasizing PRs with labels, metadata, and categorization, which is distinct from get_changes_between_refs and get_release_summary.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: when you need merged PRs between two refs, with the additional distinction that only merged PRs are included. However, it does not explicitly name alternatives or state when not to use this tool, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_release_summaryGet Release SummaryA
Generate a structured release context object ready for AI synthesis into release notes. Combines commit data, PR metadata, linked issues, contributor list, and aggregate statistics for the range between two tags.
| Name | Required | Description | Default |
|---|---|---|---|
| repo | Yes | GitHub repository name | |
| owner | Yes | GitHub repository owner (user or organization) | |
| to_tag | Yes | The new release tag or HEAD (head / newer ref) | |
| from_tag | Yes | The previous release tag (base / older ref) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It transparently describes behavior by listing what data the tool combines and clarifying that the output is a structured object intended for synthesis. It does not discuss side effects, rate limits, or edge cases, but 'Generate' and the aggregation wording sufficiently signal a read-only, non-destructive operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It front-loads the core purpose and then efficiently enumerates the combined data sources, giving the agent maximum signal per word.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, but the description compensates by naming the output type and its major components. The four required parameters are fully covered by the schema. Some detail about output shape or edge cases is absent, but the description is complete enough for an agent to select and invoke the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds only the 'range between two tags' framing, which reinforces from_tag and to_tag semantics but does not meaningfully expand on what the schema already documents for owner, repo, from_tag, or to_tag.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('Generate'), a specific resource ('structured release context object'), and the scope ('range between two tags'). It also lists concrete contents (commit data, PR metadata, linked issues, contributors, aggregate statistics), which clearly distinguishes it from sibling tools focused on individual data types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'ready for AI synthesis into release notes' gives a clear context for when to use the tool. It does not explicitly name sibling alternatives or state when not to use them, but the 'Combines...' clause implies that this is the aggregate choice when multiple data sources are needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
3 tool updates
v0.6.1- First observed
get_changes_between_refs - First observed
get_pull_requests_in_range - First observed
get_release_summary
TDQS
Scored across 3 tools
The three tools are largely distinct: one fetches commits, one fetches PRs, and one combines both into a summary. However, get_changes_between_refs and get_pull_requests_in_range both retrieve PR-related data, which could cause slight confusion for an agent deciding between them. The descriptions provide enough clarity to mitigate overlap.
All tool names follow a consistent 'get_' verb prefix followed by descriptive noun phrases in snake_case (changes_between_refs, pull_requests_in_range, release_summary). This pattern is predictable and aligns with common conventions.
With only 3 tools, the server is lean but each tool serves a clear purpose in the release-intel workflow: retrieving commits, retrieving PRs, and generating a summary. The count is minimal yet sufficient for the stated domain, though it sits at the low end of the ideal range.
The server covers the core operations for generating release context: commits, PRs, and a combined summary. However, there is no tool to list available tags/refs, which would be a natural precursor to using the other tools, and no way to directly fetch issues outside of PRs. These gaps could require agents to work around them.
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