Multi-MCP
PYPI · MULTI-MCP · SCANNED SEP 20
Multi-model AI orchestration MCP server with code review, compare, and debate tools.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs setuptools.build_meta at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
- 5 of 68 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency31
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- License check failed: no license is declared. See how to fix → Fail
- Actively maintained (last published 271 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability73
- 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
- AI-judged instruction clarity (good).Pass
- Context-footprint check failed: tool/resource definitions use about 1801 tokens (~300/item across 6 items; 6 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management80
- Stability observed for 24 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 6 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 6 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a current MCP spec version (2026-07-28).Pass
How do I install the Multi-MCP server?
Multi-MCP runs locally as a PyPI package, launched with uvx multi-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · multi-mcp
claude mcp add religa-multi-mcp -- uvx multi-mcp
{
"mcpServers": {
"religa-multi-mcp": {
"command": "uvx",
"args": [
"multi-mcp"
]
}
}
} {
"servers": {
"religa-multi-mcp": {
"command": "uvx",
"args": [
"multi-mcp"
]
}
}
} codex mcp add religa-multi-mcp -- uvx multi-mcp
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"religa-multi-mcp": {
"type": "local",
"command": [
"uvx",
"multi-mcp"
],
"enabled": true
}
}
} openclaw mcp add religa-multi-mcp --command uvx --arg multi-mcp
mcp_servers:
religa-multi-mcp:
command: "uvx"
args: ["multi-mcp"] {
"McpServers": {
"religa-multi-mcp": {
"Transport": "stdio",
"Command": "uvx",
"Arguments": [
"multi-mcp"
]
}
}
} assistant mcp add religa-multi-mcp -t stdio -c uvx -a multi-mcp
{
"mcpServers": {
"religa-multi-mcp": {
"command": "uvx",
"args": [
"multi-mcp"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 20 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 77 to 80. That category is still filling its 30-day observation window: 23 days of observed history at the previous scan, 24 at this one. The score rises as the window fills, whether or not the server changes.
- 19 Sept 26 −3
- Stability: pass → 0.77 functional
- 18 Sept 26 0
- Stability: 0.97 → pass security
- 17 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
- 15 Sept 26 +15
- Malware scan: unverified → pass ▲ security
- 14 Sept 26 −14
- Malware scan: pass → unverified ▼ security
- Security disclosure: unverified → fail ▼ functional
- 13 Sept 26 −2
- Security disclosure: fail → unverified ▼ functional
- Stability: pass → 0.83 functional
- 12 Sept 26 0
- Stability: 0.97 → pass security
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 20 Sept 2026 · Analysed pypi/multi-mcp@0.1.1
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | pypi |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | setuptools.build_meta |
Background: Why install scripts are a supply-chain risk →
Dependencies 68 packages
| Packages resolved | 68 |
|---|---|
| Stale | 5 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
chat Chat ~366
General chat with AI assistant. Supports multi-turn conversations with project context and file inclusion.
| Name | Type | Req | Description |
|---|---|---|---|
| base_path | string | yes | Absolute path to project root to id the project and load project files |
| content | string | yes | Your question to the AI Assistant. Provide detailed context: your goal, what you've tried, what worked, any specific challenges. IMPORTANT: Always include paths to relevant files in `relevant_files`… |
| model | string | – | LLM Model name to use (default: gpt-5-mini) |
| name | string | yes | Step name (e.g., 'Initial Analysis', 'Security Review') |
| next_action | string | yes | Recommended next action: 'continue' to proceed, 'stop' to end |
| relevant_files | – | – | Absolute paths of ALL files relevant to this question (up to 100 files). CRITICAL: For project-level questions (features, architecture, design), you MUST include project documentation (README.md, doc… |
| step_number | integer | yes | Current step |
| thread_id | – | – | Thread ID to continue previous conversation and preserve context. WHEN TO USE: - None/omit: Starting a brand new review or chat session (step_number=1) - Provide thread_id: Continuing a multi-step wo… |
Structured output declared, but exposes no named fields.
No examples provided.
codereview Codereview ~581
Systematic code review using external models. Covers quality, security, performance, and architecture.
| Name | Type | Req | Description |
|---|---|---|---|
| base_path | string | yes | Absolute path to project root to id the project and load project files |
| content | string | yes | Your code review request for the expert reviewer. Step 1: Describe the project and define review objectives and focus areas. Step 2+: Report findings organized by quality, security, performance, arch… |
| issues_found | – | – | REQUIRED: List of issues identified with severity levels, locations, and detailed descriptions. IMPORTANT: This list is CUMULATIVE across steps. Include ALL issues found in previous steps PLUS new on… |
| models | array | – | List of LLM models to run in parallel (minimum 1) (will use default models (['gpt-5-mini', 'gemini-3-flash']) if not specified) |
| name | string | yes | Step name (e.g., 'Initial Analysis', 'Security Review') |
| next_action | string | yes | Recommended next action: 'continue' to proceed, 'stop' to end |
| relevant_files | – | – | Absolute paths of ALL files relevant to this question (up to 100 files). CRITICAL: For project-level questions (features, architecture, design), you MUST include project documentation (README.md, doc… |
| step_number | integer | yes | Current step |
| thread_id | – | – | Thread ID to continue previous conversation and preserve context. WHEN TO USE: - None/omit: Starting a brand new review or chat session (step_number=1) - Provide thread_id: Continuing a multi-step wo… |
Structured output declared, but exposes no named fields.
No examples provided.
compare Compare ~402
Compare responses from multiple AI models. Runs the same content against all specified models in parallel. Supports multi-turn conversations with project context and file inclusion.
| Name | Type | Req | Description |
|---|---|---|---|
| base_path | string | yes | Absolute path to project root to id the project and load project files |
| content | string | yes | Your question to the AI Assistant. Provide detailed context: your goal, what you've tried, what worked, any specific challenges. IMPORTANT: Always include paths to relevant files in `relevant_files`… |
| models | array | – | List of LLM models to run in parallel (minimum 2) (will use default models (['gpt-5-mini', 'gemini-3-flash']) if not specified) |
| name | string | yes | Step name (e.g., 'Initial Analysis', 'Security Review') |
| next_action | string | yes | Recommended next action: 'continue' to proceed, 'stop' to end |
| relevant_files | – | – | Absolute paths of ALL files relevant to this question (up to 100 files). CRITICAL: For project-level questions (features, architecture, design), you MUST include project documentation (README.md, doc… |
| step_number | integer | yes | Current step |
| thread_id | – | – | Thread ID to continue previous conversation and preserve context. WHEN TO USE: - None/omit: Starting a brand new review or chat session (step_number=1) - Provide thread_id: Continuing a multi-step wo… |
Structured output declared, but exposes no named fields.
No examples provided.
debate Debate ~409
Multi-model debate: Step 1 (independent answers) + Step 2 (debate/critique). Each model provides independent answer, then reviews all responses and votes.
| Name | Type | Req | Description |
|---|---|---|---|
| base_path | string | yes | Absolute path to project root to id the project and load project files |
| content | string | yes | Your question to the AI Assistant. Provide detailed context: your goal, what you've tried, what worked, any specific challenges. IMPORTANT: Always include paths to relevant files in `relevant_files`… |
| models | array | – | List of LLM models to run in parallel (minimum 2) (will use default models (['gpt-5-mini', 'gemini-3-flash']) if not specified) |
| name | string | yes | Step name (e.g., 'Initial Analysis', 'Security Review') |
| next_action | string | yes | Recommended next action: 'continue' to proceed, 'stop' to end |
| relevant_files | – | – | Absolute paths of ALL files relevant to this question (up to 100 files). CRITICAL: For project-level questions (features, architecture, design), you MUST include project documentation (README.md, doc… |
| step_number | integer | yes | Current step |
| thread_id | – | – | Thread ID to continue previous conversation and preserve context. WHEN TO USE: - None/omit: Starting a brand new review or chat session (step_number=1) - Provide thread_id: Continuing a multi-step wo… |
Structured output declared, but exposes no named fields.
No examples provided.
models Models ~23
List available AI models. Returns model names, aliases, provider, and configuration.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
version Version ~20
Get server version, configuration details, and list of available tools.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
What is the Multi-MCP server?
Multi-MCP is listed in the public MCP registry as io.github.religa/multi-mcp. Multi-model AI orchestration MCP server with code review, compare, and debate tools. This page covers its PyPI package (multi-mcp).
Is the Multi-MCP server safe to use?
Multi-MCP scores 79 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. 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 Multi-MCP server expose?
Multi-MCP exposes 6 tools: codereview, chat, compare, debate, version, models. Their descriptions and schemas cost roughly 1,801 tokens of context every time the server is loaded.
Is the Multi-MCP server still maintained?
Multi-MCP is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.