A
licenseB
qualityA
maintenanceA meta-MCP server that manages and aggregates other MCP servers, enabling LLMs to dynamically extend their own capabilities by searching for, adding, and configuring tool servers.
16
148 PyPI
144
AGPL 3.0
rei-meta-mcp
by fc0web
rei-meta-mcp
Capa meta que se sitúa sobre el conjunto de conectores. Considera cada conector MCP un objeto y la ruta de acceso a ese objeto como un morfismo, y maneja esa estructura.
El único propósito práctico de la Fase 1 es la comprobación de coherencia (coherence check): cotejar mecánicamente si el contenido coincide entre varias fuentes que apuntan al mismo objeto.
Por qué se creó
El 19 de agosto de 2026, durante la implementación de rei-memory-mcp, se descubrió que SEED_KERNEL llevaba 11 días desviado en 1,677 vs 1,675 sin que nadie se hubiera dado cuenta. Solo se notó porque una persona comparó por casualidad las dos cifras; la máquina no tenía ningún medio de detección.
La primera tarea de este conector es que la máquina lo detecte antes que nadie. Detalles en docs/incident-2026-08-19.md.
Related MCP server: Code-Oracle
Herramientas proporcionadas (3)
meta_list_sources(object_name?: str)
Enumera las fuentes registradas y devuelve el estado de alcance, el recuento y el hash del git HEAD de cada una (indicio de frescura).
meta_check_cocherance(object_name: str, detail: bool = False)
Compara las huellas de las fuentes que apuntan al mismo objeto y devuelve un veredicto entre los siguientes:
verdict | significado |
| Coinciden las huellas de todas las fuentes alcanzadas |
| Hay discrepancias entre las fuentes alcanzadas |
| Se alcanzó cero fuentes |
| Solo se alcanzó una fuente (imposible comparar) |
§4 rule central: «no alcanzado» no es «coincidido». unreachable y single_source siempre se muestran como advertencia.
Con detail=True devuelve la lista real de IDs en discordancia (máximo 100).
meta_compose(state: from_source: str, to_source: str)
En la Fase 1 solo se compara las cadenas de texto output_schema / input_schema dentro del registro. La inferencia real del esquema es de la Fase 3 en adelante.
Lo que no se hace en la Fase 1
Reparación automática (exclusión deliberada: la decisión correcta la toma una persona)
Persistencia del historial de inspección (Fase 2)
Inferencia de esquema (Fase 3)
Construcciones de la teoría de categorías como funtores, adjunciones y mónadas (cuando sea necesario)
Fuentes registradas actualmente
Consultar config/sources.example.yaml:
source | kind | estado |
|
| huella completa ( |
|
| huella parcial (lanzar |
|
| el despliegue mediante remote-devices de claude.ai no se puede sondear directamente desde Python; siempre se indicará explícitamente |
Instalación y uso
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La ruta del registro se puede sobreescribir con la variable de entorno REI_META_MCP_REGISTRY.
Alcance honesto
Detect only, do not repair — la decisión no se saca del ámbito del humano.
Un offender
partial fingerprint(mcp_stdio) solo confirma que no hay diferencias, no constituye una prueba de «coincidencia total» (hay partes que no se ven a nivel decontent_hash).Solo cinco conceptos de teoría de categorías tienen peso propio: objeto, morfismo, igualador, composición e identidad. Evitamos el resto.
Seres el actual es un spike de la Fase 1 con 3 fuentes; la estructura gana valor cuantos más objetos haya.
La Fase 2 (historial, ejecución periódica, notificación) y la Fase 3 (inferencia de esquema, generalización de morfismos) se decidirán cuando la Fase 1 funcione en producción real.
Licencia
AGPL-3-3.0-or-later.
Relacionados
docs/incident-2026-08-19.md— registro del incidentetests/test_incident_2026_08_19.py— prueba que reproduce el incident
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.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| detail | No | ||
| object_name | Yes |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
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
| Name | Required | Description | Default |
|---|---|---|---|
| to_source | Yes | ||
| from_source | Yes |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
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
| Name | Required | Description | Default |
|---|---|---|---|
| object_name | No |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
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.
3 tool updates
v0.1.0-alpha- First observed
meta_check_coherence - First observed
meta_compose - First observed
meta_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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