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rei-meta-mcp

by fc0web

rei-meta-mcp

连接器群之上的元层。将各个 MCP 连接器视为对象,将访问对象的路径视为射,并处理其结构。

Phase 1 的唯一实用目的是一致性检查 (coherence check) — 机械地比对指向同一对象的多个来源之间的内容是否一致。

为什么做这个

2026-08-19,在 rei-memory-mcp 的实现过程中,发现 SEED_KERNEL 在 1,677 vs 1,675 上偏差了 11 天而未被察觉。之所以能发现,是因为人类偶然对比了两个数字,机器没有检测手段。

这个连接器的第一项工作,就是让机器先发现这类问题。详见 docs/incident-2026-08-19.md。

Related MCP server: Code-Oracle

提供的 tool (3 个)

meta_list_sources(object_name?: str)

枚举已注册的 source,并返回各自的到达状态、数量、git HEAD 哈希(作为 freshness 的线索)。

meta_check_coherence(object_name: str, detail: bool = False)

比对指向同一对象的 source 的指纹,返回以下 verdict 之一:

verdict

含义

coherent

所有可达 source 的指纹一致

divergent

可达 source 之间存在不一致

unreachable

可达 source 为零

single_source

仅有一个可达 source(无法比较)

§4 核心规则:“未到达”不等于“一致”。unreachable 和 single_source 始终作为警告被 surface。

detail=True 时返回不一致 ID 的实际列表(最多 100 条)。

meta_compose(from_source: str, to_source: str)

Phase 1 仅进行 registry 内 output_schema / input_schema 字符串比对。实际 schema 推断在 Phase 3 及以后。

Phase 1 不做的事

  • 自动修复(有意排除。哪个正确由人类判断)

  • 检查历史的持久化(Phase 2)

  • schema 推断(Phase 3)

  • 函子、伴随、单子等范畴论结构(需要时再说)

当前已注册的 source

参见 config/sources.example.yaml:

source

kind

状态

rei-memory-local

sqlite

full fingerprint (~/rei-memory-mcp/data/seed_kernel.db)

rei-aios-local-mcp

mcp_stdio

partial fingerprint (通过 subprocess 启动 node dist/mcp/start-mcp.js 并调用 get_kernel_status)

rei-aios-remote

unreachable_placeholder

通过 claude.ai remote-devices 的 deploy 无法从 Python 直接 probe — 始终明确标记为 unreachable

Install & 使用

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

registry 的路径可通过环境变量 REI_META_MCP_REGISTRY 覆盖。

Honest scope

  1. 仅检测,不修复 — 不将判断交给机器

  2. partial fingerprint 的 source (mcp_stdio) 之间的一致,只是“没有不一致”的确认,而非“完全一致”的证明(存在 content_hash 级别看不到的部分)

  3. 范畴论术语只承担 5 个(对象、射、等化子、合成、恒等射)。其他避免使用

  4. 当前是 3 个 source 的 Phase 1 spike。对象越多,价值越大的结构

  5. Phase 2(历史、定期执行、通知)和 Phase 3(schema 推断、射的泛化)在 Phase 1 实际运行有效后再决定

License

AGPL-3.0-or-later.

相关

  • docs/incident-2026-08-19.md — 事故记录

  • tests/test_incident_2026_08_19.py — 复现事故的测试

Available Tools

3 tools
meta_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.

ParametersJSON Schema
NameRequiredDescriptionDefault
detailNo
object_nameYes

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

B3.4/5.0
Behavior4/5

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.

Conciseness4/5

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.

Completeness3/5

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.

Parameters2/5

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.

Purpose4/5

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.

Usage Guidelines3/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
to_sourceYes
from_sourceYes

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A3.6/5.0
Behavior4/5

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.

Conciseness5/5

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.

Completeness4/5

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.

Parameters3/5

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.

Purpose4/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
object_nameNo

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A3.8/5.0
Behavior3/5

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.

Conciseness5/5

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.

Completeness3/5

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.

Parameters2/5

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.

Purpose5/5

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.

Usage Guidelines4/5

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.

  1. 3 tool updatesv0.1.0-alpha
    • First observedmeta_check_coherence
    • First observedmeta_compose
    • First observedmeta_list_sources

TDQS

A3.9/5.0

Scored across 3 tools

Disambiguation5/5

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.

Naming Consistency5/5

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.

Tool Count5/5

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.

Completeness4/5

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.

Maintenance

ActivityMaintained
ResponsivenessNo issues

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