Deep Agentic Core MCP
PYPI · DEEP-AGENTIC-CORE-MCP · SCANNED SEP 20
Unified MCP server for AgenticLens and Agentic Chaos capabilities.
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 hatchling.build at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
- 1 of 29 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency48
- 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
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 41 days ago).Pass
- Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability63
- 60% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Partial
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 550 tokens (~39/item across 14 items; 12 tools + 2 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management93
- Stability observed for 28 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage80
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 40% of tool parameters carry a description.Partial
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 12 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 13 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 Deep Agentic Core MCP server?
Deep Agentic Core MCP runs locally as a PyPI package, launched with uvx deep-agentic-core-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 · deep-agentic-core-mcp
claude mcp add deepagentlabs-deep-agentic-core-mcp -- uvx deep-agentic-core-mcp
{
"mcpServers": {
"deepagentlabs-deep-agentic-core-mcp": {
"command": "uvx",
"args": [
"deep-agentic-core-mcp"
]
}
}
} {
"servers": {
"deepagentlabs-deep-agentic-core-mcp": {
"command": "uvx",
"args": [
"deep-agentic-core-mcp"
]
}
}
} codex mcp add deepagentlabs-deep-agentic-core-mcp -- uvx deep-agentic-core-mcp
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"deepagentlabs-deep-agentic-core-mcp": {
"type": "local",
"command": [
"uvx",
"deep-agentic-core-mcp"
],
"enabled": true
}
}
} openclaw mcp add deepagentlabs-deep-agentic-core-mcp --command uvx --arg deep-agentic-core-mcp
mcp_servers:
deepagentlabs-deep-agentic-core-mcp:
command: "uvx"
args: ["deep-agentic-core-mcp"] {
"McpServers": {
"deepagentlabs-deep-agentic-core-mcp": {
"Transport": "stdio",
"Command": "uvx",
"Arguments": [
"deep-agentic-core-mcp"
]
}
}
} assistant mcp add deepagentlabs-deep-agentic-core-mcp -t stdio -c uvx -a deep-agentic-core-mcp
{
"mcpServers": {
"deepagentlabs-deep-agentic-core-mcp": {
"command": "uvx",
"args": [
"deep-agentic-core-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.
- 18 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 83 to 87. That category is still filling its 30-day observation window: 25 days of observed history at the previous scan, 26 at this one. The score rises as the window fills, whether or not the server changes.
- 17 Sept 26 +1
- Security disclosure: unverified → pass ▲ functional
- 16 Sept 26 −3
- Security disclosure: pass → unverified ▼ functional
- Stability: pass → 0.80 functional
- 15 Sept 26 0
- Stability: 0.97 → pass security
- 14 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.
- 12 Sept 26 +1
- Security disclosure: unverified → pass ▲ functional
- 11 Sept 26 0
- Security disclosure: pass → unverified ▼ functional
- 9 Sept 26 −2
- Stability: pass → 0.80 functional
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/deep-agentic-core-mcp@0.2.0
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 | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 29 packages
| Packages resolved | 29 |
|---|---|
| No linked repository | 1 |
| 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 →
chaos.list_faults List Chaos Faults ~19
List the supported fault types for chaos experiments.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
chaos.run_experiment Run Chaos Experiment ~78
Run a workspace-sandboxed target script under selected chaos faults and report the resulting events.
| Name | Type | Req | Description |
|---|---|---|---|
| faults | array | yes | – |
| script | string | yes | Script path, resolved inside the workspace root. |
| session_id | string | – | Session to read/write shared state under. Defaults to 'default'. |
| timeout_seconds | number | – | – |
No output schema declared.
No examples provided.
core.health Health Check ~27
Return rich server diagnostics: adapter availability, loaded tools/resources/prompts, and recent successful calls.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
core.session_state Session State ~40
Inspect the artifacts and call history accumulated in a session.
| Name | Type | Req | Description |
|---|---|---|---|
| session_id | string | – | Session to read/write shared state under. Defaults to 'default'. |
No output schema declared.
No examples provided.
core.verify Verify Integrations ~30
Check connectivity to agenticlens, agentic-chaos, and ai-operations-spec, and report readiness.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
core.version Server Version ~15
Return the current server package version.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
lens.analyze_workflow Analyze Workflow ~47
Analyze an AgenticLens-compatible workflow artifact.
| Name | Type | Req | Description |
|---|---|---|---|
| artifact | object | yes | – |
| session_id | string | – | Session to read/write shared state under. Defaults to 'default'. |
No output schema declared.
No examples provided.
lens.audit_report Audit Report ~55
Return case-by-case evaluation detail for an audit trail.
| Name | Type | Req | Description |
|---|---|---|---|
| include_html | boolean | – | – |
| report | object | yes | – |
| session_id | string | – | Session to read/write shared state under. Defaults to 'default'. |
No output schema declared.
No examples provided.
lens.compare_runs Compare Runs ~78
Compare baseline and candidate trace runs for regressions. 'baseline'/'candidate' may be omitted to reuse the session's stored runs.
| Name | Type | Req | Description |
|---|---|---|---|
| baseline | array | – | – |
| candidate | array | – | – |
| regression_threshold | number | – | – |
| session_id | string | – | Session to read/write shared state under. Defaults to 'default'. |
No output schema declared.
No examples provided.
lens.report_summary Workflow Report Summary ~59
Render a Markdown workflow report and recommendation summary. 'artifact' may be omitted to reuse the session's stored workflow.
| Name | Type | Req | Description |
|---|---|---|---|
| artifact | object | – | – |
| session_id | string | – | Session to read/write shared state under. Defaults to 'default'. |
No output schema declared.
No examples provided.
lens.slo_summary SLO Summary ~57
Apply release-gate style SLO thresholds to an evaluation report.
| Name | Type | Req | Description |
|---|---|---|---|
| report | object | yes | – |
| session_id | string | – | Session to read/write shared state under. Defaults to 'default'. |
| thresholds | object | – | – |
No output schema declared.
No examples provided.
spec.validate_artifact Validate AI Operations Artifact ~33
Validate a workflow or run artifact against the AI Operations v0.4 draft.
| Name | Type | Req | Description |
|---|---|---|---|
| artifact | object | yes | – |
No output schema declared.
No examples provided.
What is the Deep Agentic Core MCP server?
Deep Agentic Core MCP is listed in the public MCP registry as io.github.DeepAgentLabs/deep-agentic-core-mcp. Unified MCP server for AgenticLens and Agentic Chaos capabilities. This page covers its PyPI package (deep-agentic-core-mcp).
Is the Deep Agentic Core MCP server safe to use?
Deep Agentic Core MCP scores 80 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 Deep Agentic Core MCP server expose?
Deep Agentic Core MCP exposes 12 tools: core.health, core.version, core.verify, core.session_state, lens.analyze_workflow, and 7 more. Their descriptions and schemas cost roughly 538 tokens of context every time the server is loaded.
Is the Deep Agentic Core MCP server still maintained?
Deep Agentic Core 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.
What licence is the Deep Agentic Core MCP server under?
Deep Agentic Core MCP declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.