rei-meta-mcp
rei-meta-mcp
Мета-уровень, стоящий над группой коннекторов. Рассматривает отдельные MCP-коннекторы как объекты, пути доступа к объектам — как морфизмы, и работает с этой структурой.
Зачем это сделано
2026-08-19 в процессе реализации rei-memory-mcp выяснилось, что SEED_KERNEL расходился на 1,677 против 1,675 и оставался незамеченным в течение 11 дней. Заметить это смог только человек, случайно сравнив оба числа, — у машины не было средств обнаружения.
Первая задача этого коннектора — чтобы машина обнаруживала это первой. Подробности: docs/incident-2026-08-19.md.
Related MCP server: Code-Oracle
Предоставляемые инструменты (3 шт.)
meta_list_sources(object_name?: str)
Перечисляет зарегистрированные source и возвращает для каждого состояние достижимости, количество записей и хэш HEAD (как признак свежести).
meta_check_coherence(object_name: str, detail: bool = False)
Сверяет отпечатки source, указывающих на один и тот же объект, и возвращает один из следующих вердиктов:
вердикт | значение |
| отпечатки всех достижимых source совпадают |
| среди достижимых source есть расхождения |
| достижимых source нет |
| достижим только один source (сравнение невозможно) |
Основное правило: «недостижимо» — это не «совпадает». unreachable и single_source всегда отображаются как предупреждение.
При detail=True возвращается фактический список идентификаторов с расхождениями (максимум 100 записей).
meta_compose(from_source: str, to_source: str)
На этапе 1 — только сопоставление строк output_schema / input_schema в реестре. Вывод фактической схемы — начиная с этапа 3.
Что не делается на этапе 1
Автоматическое исправление (намеренно исключено; решение о том, что верно, принимает человек)
Сохранение истории проверок (этап 2)
Вывод схемы (этап 3)
Конструкции теории категорий — функторы, сопряжения, монады и т.п. (если возникнет необходимость)
Текущие зарегистрированные source
См. config/sources.example.yaml:
source | kind | состояние |
|
| полный отпечаток ( |
|
| частичный отпечаток (запуск |
|
| недоступен — заглушка; через |
Установка и использование
uv pip install -e ".[dev]"
cp config/sources.example.yaml config/sources.yaml # パスを埋める
uv run pytest # 全 PASS を確認
uv run rei-meta-mcp # stdio で MCP server 起動Путь к реестру можно переопределить переменной окружения REI_META_MCP_REGISTRY.
Честная область применения
Только обнаружение, без исправления — решение остаётся за человеком.
Частичный отпечаток для source типа
mcp_stdio— это подтверждение отсутствия расхождений, а не доказательство полного совпадения (не проверяются части, не покрытыеcontent_hash).Терминология теории категорий — только пять терминов (объект, морфизм, уравнитель, композиция, тождественный морфизм); никакой дополнительной нагрузки.
Сейчас — 3 source, этап 1 — ценность растёт по мере увеличения числа объектов.
Этап 2 (история, регулярные проверки) и этап 3 (вывод схемы, морфизмы) — только после того, как этап 1 заработает в реальной эксплуатации.
Лицензия
AGPL-3.0-or-later.
Связанные материалы
docs/incident-2026-08-19.md— запись об инцидентеtests/test_incident_2026_08_19.py— тест, воспроизводящий инцидент
Available Tools
3 toolsmeta_check_coherenceB
Check whether all sources for object_name agree.
Verdicts: coherent | divergent | unreachable | single_source. §4: unreachable/single_source are warnings, not silent success.
| Name | Required | Description | Default |
|---|---|---|---|
| detail | No | ||
| object_name | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It goes beyond a simple 'check' by specifying the possible verdicts and the important warning semantics for `unreachable` and `single_source`, which is non-obvious. It does not discuss side effects, but as a read-only check that is reasonably implied.
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 short, front-loads the main purpose, and uses a compact verdict list plus a warning note. The only minor issue is the cryptic '§4' reference, which is terse but may require external 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?
The core purpose and output verdicts are covered, and the presence of an output schema reduces the need to describe return structure. However, key gaps remain: the `detail` parameter is unexplained, and there is no guidance on choosing this tool over its siblings.
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 description clarifies that `object_name` is the object whose sources are checked, but it says nothing about the `detail` boolean parameter. Since schema description coverage is 0%, the description needed to compensate but only explains one of the two parameters.
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 states a specific action ('Check whether all sources agree') on a specific resource (`object_name`), and enumerates the possible verdicts. It does not explicitly differentiate from sibling tools, but the verb and resource make the purpose clear enough.
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 usage is implied by 'Check whether all sources agree' — the agent can infer it is for consistency checking across sources. However, there is no explicit mention of when to prefer this tool over `meta_list_sources` or `meta_compose`, nor any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
meta_composeA
Check whether the output of from_source can feed to_source.
Phase 1: declarative schema string match only.
| Name | Required | Description | Default |
|---|---|---|---|
| to_source | Yes | ||
| from_source | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It clearly discloses that this is only a phase-1 declarative schema string match, which meaningfully sets expectations about the tool's limitations. This is useful context beyond what the schema alone provides.
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 short and front-loaded: the first sentence states the core purpose, and the second adds a critical limitation. Every sentence earns its place with no filler or repetition.
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 is simple with two string parameters and an output schema, so return-value details are not needed. The description covers the core behavior and limitation, though it leaves some contextual ambiguity about how sources are identified and when this check is appropriate relative to sibling tools.
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 gives relational meaning to both parameters: 'from_source' produces output and 'to_source' receives it. However, it does not describe the expected format or examples, leaving part of the semantics implicit.
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 states a specific action ('Check whether the output... can feed...') and identifies the two resources involved. It is clear about the compositional relationship, though it does not explicitly differentiate itself from the sibling tool meta_check_coherence.
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 explicit guidance explains when to use this tool versus meta_list_sources or meta_check_coherence. The phrase 'Phase 1: declarative schema string match only' implies a preliminary check, but it never states conditions, exclusions, or recommended alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
meta_list_sourcesA
List registered sources with current reachability and freshness.
| Name | Required | Description | Default |
|---|---|---|---|
| object_name | No |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry behavioral disclosure. It conveys that the tool reports current reachability and freshness, and 'List' implies a read-only operation. However, it does not explain behavior around the optional object_name parameter, potential network/performance implications, or any side effects.
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, compact sentence that front-loads the primary action and object. Every word contributes useful information, with no redundancy or filler.
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 simple listing tool with one optional parameter and an output schema, the description provides the essential purpose and result characteristics. However, it omits parameter semantics and usage boundaries, leaving some gaps an agent would need to infer.
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% for the only parameter, and the description does not mention object_name at all. The schema gives only a type, title, and default, which is insufficient for an agent to understand how filtering by object_name works or whether it is optional.
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 uses a specific verb and resource: 'List registered sources', and adds distinguishing detail with 'current reachability and freshness'. This clearly identifies the tool's purpose and sets it apart from siblings like meta_check_coherence and meta_compose.
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: use this tool when you need an inventory of registered sources with their current status. It does not explicitly state when not to use it or point to alternatives, but sibling names are distinct enough that there is no ambiguity.
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
v0.1.0-alpha- First observed
meta_check_coherence - First observed
meta_compose - First observed
meta_list_sources
TDQS
Scored across 3 tools
Each tool has a distinct responsibility: listing registered sources, checking source agreement for an object, and validating source-to-source composability. There is minimal overlap, and the differing parameters make selection unambiguous.
All tools use the `meta_` prefix with an imperative snake_case verb (`list`, `check`, `compose`), giving a predictable convention. The slight variation in whether an object follows the verb does not hurt recognizability.
Three tools is a compact but appropriate scope for a focused metadata validation server. Each tool provides a distinct high-level capability with no redundancy.
The set covers the core discovery and validation workflows: enumerate sources, check coherence, and test composition. It is missing broader source/object management and only performs schema-string composition matching, so there are minor gaps but no dead ends for the main use case.
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