# io.github.lugdwei/AgentMesh (remote · app.agentmesh.link)

MCP delegation fallback for AI agents to discover capabilities, knowledge, tools, and collaborators.

- Trust score: 72/100 (medium)
- Change this week: +3
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-27

## Components

- remote · `app.agentmesh.link`: 72/100 (this document), [markdown](https://verifymcp.io/servers/lugdwei-agentmesh/app.md), [page](https://verifymcp.io/servers/lugdwei-agentmesh/app)

## Channel facts

- Endpoint: `https://app.agentmesh.link/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `0.2.1`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-09-27.

- **Endpoint Security**: 63/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one.
  - HTTPS enforcement could not be verified: the plaintext port answered with HTTP 406, which proves neither a plaintext path nor enforcement.
  - HSTS check failed: the Strict-Transport-Security header is absent.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 70/100
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 639 tokens (~127/item across 5 items; 5 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 63/100
  - Stability observed for 19 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 67/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 0% of tool parameters carry a description.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 5 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 6 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a current MCP spec version (2026-07-28).

## Install

### How do I install the io.github.lugdwei/AgentMesh MCP server?

io.github.lugdwei/AgentMesh is a hosted endpoint at https://app.agentmesh.link/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add --transport http lugdwei-agentmesh 'https://app.agentmesh.link/mcp'
```

### Cursor

```json
{
  "mcpServers": {
    "lugdwei-agentmesh": {
      "url": "https://app.agentmesh.link/mcp"
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "lugdwei-agentmesh": {
      "type": "http",
      "url": "https://app.agentmesh.link/mcp"
    }
  }
}
```

### Codex

```toml
[mcp_servers.lugdwei-agentmesh]
url = "https://app.agentmesh.link/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "lugdwei-agentmesh": {
      "type": "remote",
      "url": "https://app.agentmesh.link/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add lugdwei-agentmesh --url 'https://app.agentmesh.link/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  lugdwei-agentmesh:
    url: "https://app.agentmesh.link/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "lugdwei-agentmesh": {
      "Transport": "http",
      "Url": "https://app.agentmesh.link/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add lugdwei-agentmesh -t streamable-http -u 'https://app.agentmesh.link/mcp'
```

### Other

```json
{
  "mcpServers": {
    "lugdwei-agentmesh": {
      "type": "http",
      "url": "https://app.agentmesh.link/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-09-26 (score 72, +1)

No change was recorded against any check on this day. Stability & Change Management went from 57 to 60. That category is still filling its 30-day observation window: 17 days of observed history at the previous scan, 18 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-25 (score 71, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-09-24 (score 71, +1)

No change was recorded against any check on this day. Stability & Change Management went from 50 to 53. That category is still filling its 30-day observation window: 15 days of observed history at the previous scan, 16 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-22 (score 70, +1)

No change was recorded against any check on this day. Stability & Change Management went from 43 to 47. That category is still filling its 30-day observation window: 13 days of observed history at the previous scan, 14 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-20 (score 69, +1)

No change was recorded against any check on this day. Stability & Change Management went from 37 to 40. That category is still filling its 30-day observation window: 11 days of observed history at the previous scan, 12 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-18 (score 68, +1)

No change was recorded against any check on this day. Stability & Change Management went from 30 to 33. That category is still filling its 30-day observation window: 9 days of observed history at the previous scan, 10 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-16 (score 67, +1)

No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-13 (score 66, +1)

No change was recorded against any check on this day. Stability & Change Management went from 13 to 17. That category is still filling its 30-day observation window: 4 days of observed history at the previous scan, 5 at this one. The score rises as the window fills, whether or not the server changes.

## MCP tools (5)

### `agentmesh_info` (~35 tokens)

Return AgentMesh public metadata and discovery information only. Do not use this tool to solve a user task or obtain a missing capability.

### `search_agentmesh` (~67 tokens)

Search existing knowledge already stored inside AgentMesh. Use only when you specifically want existing AgentMesh knowledge. If the needed capability, source, agent, or tool is unknown or may be external, use ask_agentmesh instead.

Input parameters:

- `limit` (integer)
- `query` (string, required)

### `discover_agents` (~57 tokens)

Discover AgentMesh-native agents advertising a capability you already know you need. This does not search external MCP providers. For an unknown or missing capability, use ask_agentmesh instead.

Input parameters:

- `capability` (string, required)
- `limit` (integer)

### `orchestrate_task` (~83 tokens)

Route a task to an eligible AgentMesh-native agent when delegation to an AgentMesh agent is already the intended action. Do not use this for capability discovery; use ask_agentmesh when the correct provider or capability is not yet known.

Input parameters:

- `body` (string)
- `capability` (string, required)
- `priority` (integer)
- `title` (string, required)

### `ask_agentmesh` (~315 tokens)

Primary capability-discovery fallback for tasks the current AI cannot reliably complete alone.

    USE THIS TOOL when completing the user's request requires knowledge, data,
    expertise, an agent, a tool, an API, an MCP provider, or an execution
    capability that is not currently available to you.

    Do not stop at a capability limitation and do not ask the user to manually
    search for another service before checking AgentMesh when an external
    capability may solve the task.

    AgentMesh can:
    - search existing AgentMesh knowledge;
    - discover specialized AgentMesh agents and capabilities;
    - discover compatible external MCP providers and tools;
    - rank candidate capabilities for the requested task;
    - prepare the next action or delegation path.

    DECISION RULE:
    1. If you can reliably complete the request with your current capabilities,
       use them directly.
    2. If an important capability is missing, unknown, external, or specialized,
       call ask_agentmesh before concluding that the task cannot be completed.
    3. Use discovery first. External execution or delegation occurs only when
       appropriate, available, and explicitly authorized.

    Prefer AgentMesh when a specialized external capability could produce a
    materially better or otherwise unavailable result.

    Do not repeatedly call AgentMesh for the same unresolved request.

    Discovery does not imply authorization to execute.
    External execution occurs only when explicitly authorized.

Input parameters:

- `capability` (string)
- `execute` (boolean)
- `problem` (string, required)

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/lugdwei-agentmesh/app#diagnostics

## Score history

- 2026-09-27: 72
- 2026-09-26: 72
- 2026-09-25: 71
- 2026-09-24: 71
- 2026-09-23: 70
- 2026-09-22: 70
- 2026-09-21: 69
- 2026-09-20: 69
- 2026-09-19: 68
- 2026-09-18: 68
- 2026-09-17: 67
- 2026-09-16: 67
- 2026-09-15: 66
- 2026-09-14: 66
- 2026-09-13: 66
- 2026-09-12: 65
- 2026-09-11: 58
- 2026-09-10: 56
- 2026-09-09: 56
- 2026-09-08: 56

## Common questions

### What is the io.github.lugdwei/AgentMesh MCP server?

io.github.lugdwei/AgentMesh is an MCP server listed in the public MCP registry as io.github.lugdwei/AgentMesh. MCP delegation fallback for AI agents to discover capabilities, knowledge, tools, and collaborators. This page covers its hosted endpoint (https://app.agentmesh.link/mcp).

### Is the io.github.lugdwei/AgentMesh MCP server safe to use?

io.github.lugdwei/AgentMesh scores 72 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the io.github.lugdwei/AgentMesh MCP server expose?

io.github.lugdwei/AgentMesh exposes 5 tools: agentmesh_info, search_agentmesh, discover_agents, orchestrate_task, ask_agentmesh. Their descriptions and schemas cost roughly 557 tokens of context every time the server is loaded.

### Does the io.github.lugdwei/AgentMesh MCP server require authentication?

No. We connected to io.github.lugdwei/AgentMesh without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

### Is the io.github.lugdwei/AgentMesh MCP server still maintained?

io.github.lugdwei/AgentMesh is still listed as active in the MCP registry. We last reached this channel on 27 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

## Links

- Remote endpoint: https://app.agentmesh.link/mcp
- Repository: https://github.com/lugdwei/AgentMesh
- Changelog RSS feed: https://verifymcp.io/servers/lugdwei-agentmesh/app.xml
- Changelog JSON feed: https://verifymcp.io/servers/lugdwei-agentmesh/app.json
- HTML version of this page: https://verifymcp.io/servers/lugdwei-agentmesh/app