gitlog-mcp
🔍 gitlog-mcp
Дайте вашему AI-агенту суперспособности в работе с историей git.
gitlog-mcp — это MCP-сервер (Model Context Protocol), который позволяет AI-агентам (Claude Code, Cursor, Windsurf и любому MCP-клиенту) понимать что изменилось в репозитории — автоматически генерировать changelog, анализировать коммиты, определять автора изменений и составлять черновики релизных заметок.
«Что изменилось в этом репозитории?» — вопрос, на который каждый AI-агент отвечает неправильно. Это исправляет ситуацию.
Зачем это нужно
AI-агенты для программирования отлично пишут код, но печально известны тем, что не знают истории кодовой базы. Они выдумывают changelog, ошибочно приписывают авторство и угадывают релизные заметки. gitlog-mcp даёт им надёжное, структурированное окно в git log — чтобы их ответы основывались на том, что действительно произошло, а не на вымысле.
Related MCP server: Git Insight MCP
Возможности
📝 Авто-changelog — создавайте чистый, сгруппированный changelog из любого диапазона тегов/коммитов
🔎 Анализ коммитов — объясняет почему произошло изменение, а не только что изменилось
👤 Определение автора (blame) — кто что изменил и когда (с контекстом)
🏷️ Релизные заметки — черновик релизных заметок на основе различий между тегами
📊 Здоровье репозитория — частота коммитов, топ-контрибьюторы, горячие точки изменений
🧱 Нулевые зависимости времени выполнения — чистый Python stdlib + MCP SDK, один файл
Быстрый старт
# 1. Install from PyPI
pip install gitlog-mcp
# 2. Run standalone (for testing) — defaults to the current directory
gitlog-mcp
gitlog-mcp --repo /path/to/your/repo
# 3. Or add directly to your agent's MCP config (see below)Хотите также локальную веб-панель? Это опциональное дополнение, не устанавливается по умолчанию:
pip install "gitlog-mcp[ui]". Обычныйpip install gitlog-mcpостаётся без зависимостей, как и прежде.
Установка из исходного кода (для контрибьюторов):
git clone https://github.com/ManiaSacha/gitlog-mcp.git && cd gitlog-mcp && pip install -e .— подробнее в CONTRIBUTING.md.
Конфигурация Claude Code
{
"mcpServers": {
"gitlog": {
"command": "gitlog-mcp",
"args": ["--repo", "."]
}
}
}Конфигурация Cursor (.cursor/mcp.json)
{
"mcpServers": {
"gitlog": {
"command": "gitlog-mcp",
"args": ["--repo", "."]
}
}
}Конфигурация Windsurf
{
"mcpServers": {
"gitlog": {
"command": "gitlog-mcp",
"args": ["--repo", "."]
}
}
}Отладка отдельно
Хотите опробовать инструменты напрямую перед подключением к агенту? MCP Inspector предоставляет интерфейс для вызова каждого инструмента вручную:
npx @modelcontextprotocol/inspector gitlog-mcp --repo .Примеры запросов к агенту
«Сгенерируй changelog всего, что изменилось между
v1.2.0иv1.3.0».
«Кто внёс эту ошибочную строку в
src/parser.pyи почему?»
«Составь черновик релизных заметок для следующей версии на основе последних коммитов».
Доступные инструменты
Инструмент | Описание |
| Сгруппированный changelog для диапазона коммитов/тегов |
| Объясняет намерения и влияние конкретного коммита |
| Построчное определение автора для файла |
| Черновик релизных заметок между двумя тегами |
| Сводка по контрибьюторам и изменениям |
| Поиск коммитов по сообщению/автору/дате |
Веб-панель (опционально)
Предпочитаете браузер терминалу? gitlog-mcp-ui предоставляет небольшую локальную панель на основе того же кода для чтения git, что и MCP-инструменты — те же данные, человекочитаемый формат.
pip install "gitlog-mcp[ui]"
gitlog-mcp-ui --repo /path/to/repoКоманда выводит URL (http://127.0.0.1:8765 по умолчанию) — откройте его в браузере; панель не откроет его за вас.
Вид | Что показывает |
Changelog | Выбор диапазона коммитов ( |
Repo Health | Статистика контрибьюторов, общее количество коммитов |
Blame | Построчное определение автора для каждого файла |
Только чтение — никаких действий записи. Построена только для локального использования: привязывается только к 127.0.0.1 (нет флага --host, поэтому её нельзя случайно открыть для сети), а также проверяет заголовок Host каждого запроса, закрывая возможность DNS-ребендинга, которую не покрывает только loopback-привязка. Аутентификация не требуется, потому что до неё может добраться только ваша собственная машина.
Это опциональное дополнение (pip install gitlog-mcp[ui]), не устанавливается по умолчанию. Основной сервер gitlog-mcp не имеет зависимостей времени выполнения, кроме MCP SDK, точка — панель это не меняет. Это http.server из stdlib, никакого фреймворка, никаких дополнительных зависимостей.
Архитектура
gitlog-mcp (single file, ~300 lines)
├── FastMCP server (stdio transport)
├── GitRunner — thin wrapper over `git` CLI
└── Tools — each maps to a git subcommand + parsingНамеренно компактная. Вы можете прочитать всё за полдня — это особенность.
Участие в разработке
PR приветствуются. Только маленькие, целенаправленные, хорошо протестированные изменения. См. CONTRIBUTING.md.
Процесс релиза и версионирование описаны в RELEASING.md.
План развития
Автоопределение
--repoиз текущей директорииСтруктурированный JSON-вывод для всех инструментов
Интеграция с GitHub/GitLab
Тесты + значок CI
Лицензия
MIT © 2026 — создано в открытую, для сообщества открытого кода.
Поставьте звезду этому репозиторию, если хотите, чтобы AI-агенты перестали выдумывать ваш changelog. ⭐
Available Tools
6 toolsanalyze_commitC
Explain a specific commit's intent and impact.
| Name | Required | Description | Default |
|---|---|---|---|
| sha | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It only says 'explain intent and impact' without disclosing whether the analysis is AI-generated, static, or requires external calls. It does not state if the tool is read-only or if it has side effects. The description adds minimal behavioral context beyond the tool name.
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 of 6 words, which is efficient but at the cost of critical information. While it avoids redundancy, it does not earn its place because it omits parameter details and usage guidance. For a tool with one parameter and no annotations, a slightly longer but more informative description would be better.
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?
The tool has an output schema (not shown), so return values need not be described. However, with a single parameter and no parameter description, the description is incomplete. The agent can infer the parameter's purpose from the tool name, but the lack of any parameter guidance makes it minimally adequate. Sibling tools are listed but not referenced.
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?
The input schema has one parameter 'sha' with no description (0% schema coverage). The description does not mention this parameter, leaving the agent to infer that 'sha' is a commit hash. No format, examples, or constraints are provided. The description adds no value beyond the schema, which already lacks detail.
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 action ('explain') and the resource ('a specific commit'), and specifies the scope ('intent and impact'). It distinguishes from sibling tools like 'changelog' (list changes) and 'search_commits' (multiple commits) by focusing on a single commit's reasoning. However, it could explicitly mention the SHA parameter to reinforce the single-commit scope.
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?
No guidance is provided on when to use this tool versus alternatives. Siblings like 'blame_file' or 'repo_health' serve different purposes, but the description does not explicitly state when to prefer 'analyze_commit' over 'changelog' or 'search_commits' for understanding a commit. The agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
blame_fileC
Line-level attribution for a file (who, when, which commit).
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure but only states the output content (who, when, which commit). It does not reveal constraints such as requiring a tracked file, performance implications, or whether the blame is for the latest commit only.
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 fluff. While concise, it is slightly under-specific (e.g., missing 'Returns blame information for each line'), but every word contributes to the core purpose.
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?
Given the tool's simplicity (one required parameter and an output schema), the description is minimally adequate. However, it omits context such as the requirement that the file be part of a Git repository and could benefit from a brief note on expected input format.
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?
The schema has 0% description coverage and the single parameter 'path' is not elaborated in the description. The description adds no meaning beyond the schema, failing to specify that the path should be relative to the repository root or that the file must exist in the version history.
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 'Line-level attribution for a file (who, when, which commit)' clearly states the tool's purpose using a specific verb ('attribution') and resource ('file'). It distinguishes the tool from siblings like changelog and search_commits by focusing on per-line metadata.
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 no guidance on when or when not to use this tool versus alternatives. No conditions, prerequisites, or exclusions are mentioned, leaving the agent to infer usage solely from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
changelogC
Generate a grouped changelog for a commit range (e.g. v1.2.0..v1.3.0).
| Name | Required | Description | Default |
|---|---|---|---|
| since | No | HEAD~20 | |
| until | No | HEAD |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only indicates the output is 'grouped', but does not mention read-only nature, authentication needs, rate limits, or side effects. The agent gains little insight beyond the basic function.
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, well-front-loaded sentence with no waste. It efficiently conveys the core action. However, the brevity sacrifices necessary detail that could be added without much length.
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?
Given two optional parameters and no annotations, the description is insufficient. Even with an output schema, the agent lacks usage guidelines and parameter semantics. The tool is simple, but the description leaves ambiguity about how to specify the range 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 0%, so the description must compensate. It mentions a commit range example ('v1.2.0..v1.3.0') which hints at the 'since' and 'until' parameters, but does not explicitly map them or explain their formats. The default values ('HEAD~20', 'HEAD') are not explained.
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 verb 'generate' and the resource 'grouped changelog', and specifies the scope 'for a commit range' with an example format. However, it does not explicitly differentiate from siblings like release_notes, though the purpose is distinct.
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?
No guidance on when to use this vs. alternative sibling tools (e.g., release_notes, search_commits). The description implies usage for commit ranges but offers no exclusions or conditional context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
release_notesC
Draft release notes between two tags.
| Name | Required | Description | Default |
|---|---|---|---|
| to_tag | Yes | ||
| from_tag | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavioral traits. It only says 'Draft release notes', which is vague—does it create a file, output text, or modify something? No side effects, authentication needs, or rate limits are mentioned, making it insufficient for safe agent execution.
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 extremely concise (one sentence, six words), which is good for quick scanning. However, it sacrifices essential information—critical details about behavior, usage, and parameters are missing, so it is not 'appropriately sized' for the tool's context.
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?
Given the tool has two required parameters, no annotations, and an output schema (which could return draft content), the description is too brief. It fails to mention what the output contains, how it behaves, or any constraints, leaving the agent underinformed for correct invocation.
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 0%, so the description must compensate. It implies that 'from_tag' and 'to_tag' define a range, but does not specify which is earlier/later or any format constraints. This minimal guidance leaves ambiguity about parameter ordering and expected values.
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 verb 'Draft' and the resource 'release notes' with scope 'between two tags', making the purpose easy to grasp. However, it does not differentiate from the sibling tool 'changelog', which may have overlapping functionality, so a 5 is not justified.
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?
No guidance is provided on when to use this tool versus alternatives like 'changelog' or 'search_commits'. There is no mention of prerequisites (e.g., tags must exist) or when not to use it, leaving the agent without contextual decision-making support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
repo_healthB
Contributor + churn summary for the repo.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full responsibility for disclosing behavioral traits. It only states 'Contributor + churn summary', implying a read operation, but does not mention safety, required permissions, rate limits, or any side effects. For a tool with zero annotation coverage, this is insufficient transparency.
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 extremely concise at one sentence, but it is vague and lacks structure. It does not front-load the most critical information (e.g., the verb or output format). While it wastes no words, it could be more informative without increasing length significantly (e.g., 'Retrieves a summary of contributor activity and churn metrics for the repository').
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?
The tool has no parameters and an output schema (existence noted), so the description does not need to detail return values. However, 'Contributor + churn summary' is vague—it does not specify the time period, metrics included, or how the summary is structured. For a tool with simple inputs, this level of completeness is minimally adequate but could be improved.
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?
The input schema has no parameters, so schema description coverage is 100% by default. The description does not need to add parameter meaning, and the baseline for 0 parameters is 4. The description is neutral—it does not contradict or enhance parameter semantics, but it is not required to.
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 'Contributor + churn summary for the repo.' clearly indicates the tool returns a summary of contributor and churn metrics. It uses a specific resource (repo) and implies a retrieval action, which distinguishes it from siblings like 'changelog' or 'analyze_commit' that focus on individual commits or logs. However, it lacks a verb (e.g., 'get' or 'retrieve') and does not explicitly contrast with siblings, slightly reducing clarity.
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?
No guidance is provided on when to use this tool versus sibling tools like 'changelog', 'analyze_commit', 'blame_file', 'release_notes', or 'search_commits'. The description does not mention context, prerequisites, or alternatives. Without any usage instructions, the agent must infer applicability from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_commitsC
Find commits by message, author, or date.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It states it can search by message, author, or date, but does not clarify how the 'query' parameter is interpreted (e.g., does it accept regex, multiple terms, or date formats?). It also does not mention potential side effects (none expected) or pagination behavior.
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 short sentence, which is concise. However, it is too brief to cover the necessary details for a tool with no annotations and low schema coverage, making it feel underspecified rather than optimally concise.
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?
Given the tool has one required parameter with no schema description, no annotations, and an output schema (details not shown), the description is incomplete. It does not explain the expected format of the 'query' parameter, the return structure, or any limitations. With sibling tools like 'analyze_commit' and 'blame_file', more context is needed to differentiate usage.
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 0%, so the description must compensate. It mentions that commits can be found by message, author, or date, but does not explain how to encode these in the single 'query' parameter (e.g., using prefixes like 'author:'). This leaves the agent guessing how to use the parameter effectively.
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 tool finds commits and specifies the search dimensions (message, author, or date). It distinguishes itself from sibling tools like 'changelog' or 'analyze_commit' by indicating a general search capability, though it could be more explicit about the scope.
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 no guidance on when to use this tool versus siblings like 'analyze_commit' (for detailed analysis) or 'changelog' (for release notes). It does not mention limitations, such as whether the search is across a repository or workspace, or what happens if no results are found.
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. Dates show when Glama detected each change.
6 tool updates
v0.1.3- First observed
analyze_commit - First observed
blame_file - First observed
changelog - First observed
release_notes - First observed
repo_health - First observed
search_commits
TDQS
Most tools have distinct purposes: changelog vs. release_notes share overlap in generating summaries from commit ranges/tags, which could cause confusion. However, the others are clearly separated.
All tool names use a consistent verb_noun pattern (changelog is a noun but functions as a verb, minor deviation). Names are clear and predictable.
6 tools is well-scoped for a Git log/analysis server, covering key operations without bloat.
Covers commit analysis, search, blame, release notes, and health metrics. A possible gap is direct diff retrieval between commits, but core workflows are well-supported.
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