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
142
AGPL 3.0
rei-meta-mcp
by fc0web
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@rei-meta-mcpCheck coherence of SEED_KERNEL across all sources."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
rei-meta-mcp
A meta-layer standing on top of the connector group. It treats individual MCP connectors as objects and access paths to those objects as morphisms, and handles their structure.
The only practical purpose of Phase 1 is coherence check — mechanically cross-checking whether the contents match across multiple sources pointing to the same object.
Why it was made
On 2026-08-19, during the implementation of rei-memory-mcp, it was discovered that SEED_KERNEL had drifted by 1,677 vs 1,675 for 11 days without being noticed. It was noticed only because a human happened to compare both numbers by chance; there was no mechanical means of detection.
The first job of this connector is to let the machine find this first. See docs/incident-2026-08-19.md for details.
Related MCP server: Code-Oracle
Provided tools (3)
meta_list_sources(object_name?: str)
Enumerates registered sources and returns each one's reachability status, count, and git HEAD hash (a clue to freshness).
meta_check_coherence(object_name: str, detail: bool = False)
Cross-checks the fingerprints of sources pointing to the same object and returns one of the following verdicts:
verdict | meaning |
| Fingerprints of all reachable sources match |
| Mismatch among reachable sources |
| Zero reachable sources |
| Only one reachable source (not comparable) |
§4 Core rule: "unreachable" is not "matched". unreachable and single_source are always surfaced as warnings.
With detail=True, returns the actual list of mismatched IDs (up to 100 items).
meta_compose(from_source: str, to_source: str)
Phase 1 only does string matching of output_schema / input_schema in the registry. Actual schema inference is Phase 3 and later.
What Phase 1 does not do
Automatic repair (intentionally excluded. Judgment of which is correct is left to humans)
Persistence of inspection history (Phase 2)
Schema inference (Phase 3)
Categorical constructions such as functors, adjunctions, monads, etc. (when the need arises)
Currently registered sources
See config/sources.example.yaml:
source | kind | status |
|
| full fingerprint ( |
|
| partial fingerprint (launches |
|
| Deployment via claude.ai remote-devices cannot be probed directly from Python — always explicitly reports |
Install & usage
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The registry path can be overridden with the environment variable REI_META_MCP_REGISTRY.
Honest scope
Detection only, no repair — does not take judgment outside of humans
Matching among partial fingerprint sources (mcp_stdio) is confirmation that "there is no mismatch", not proof of "exact match" (there are parts not visible at the
content_hashlevel)Only 5 category theory terms carry weight (object, morphism, equalizer, composition, identity morphism). Others are avoided
Currently a Phase 1 spike with 3 sources. A structure whose value increases as the number of objects grows
Phase 2 (history, scheduled execution, notifications) and Phase 3 (schema inference, generalization of morphisms) will be decided after Phase 1 works in real operation
License
AGPL-3.0-or-later.
Related
docs/incident-2026-08-19.md— record of the incidenttests/test_incident_2026_08_19.py— test that reproduces the 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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