junai Pipeline MCP
PYPI · JUNAI-MCP · SCANNED SEP 20
Agentic pipeline orchestration MCP server for AI-driven development workflows.
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 Security50
- Malware scan not yet available for this package.Unverified
- 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
- 1 of 15 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency6
- Repository check failed: the declared repository URL redirects; it must resolve directly. See how to fix → View diagnostics → Fail
- 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 50 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability69
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 565 tokens (~70/item across 8 items; 8 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management87
- Stability observed for 26 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage76
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 16% of tool parameters carry a description.Partial
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety75
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- 0 of 1 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation; "run_command" implies "execute" and declares no destructiveHint at all, which the MCP spec reads as destructive by default. See how to fix → Fail
- An AI judge read all 8 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 junai Pipeline MCP server?
junai Pipeline MCP runs locally as a PyPI package, launched with uvx junai-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 · junai-mcp
claude mcp add saajunaid-junai-mcp -- uvx junai-mcp
{
"mcpServers": {
"saajunaid-junai-mcp": {
"command": "uvx",
"args": [
"junai-mcp"
]
}
}
} {
"servers": {
"saajunaid-junai-mcp": {
"command": "uvx",
"args": [
"junai-mcp"
]
}
}
} codex mcp add saajunaid-junai-mcp -- uvx junai-mcp
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"saajunaid-junai-mcp": {
"type": "local",
"command": [
"uvx",
"junai-mcp"
],
"enabled": true
}
}
} openclaw mcp add saajunaid-junai-mcp --command uvx --arg junai-mcp
mcp_servers:
saajunaid-junai-mcp:
command: "uvx"
args: ["junai-mcp"] {
"McpServers": {
"saajunaid-junai-mcp": {
"Transport": "stdio",
"Command": "uvx",
"Arguments": [
"junai-mcp"
]
}
}
} assistant mcp add saajunaid-junai-mcp -t stdio -c uvx -a junai-mcp
{
"mcpServers": {
"saajunaid-junai-mcp": {
"command": "uvx",
"args": [
"junai-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.
- 19 Sept 26 −2
- Stability: pass → 0.83 functional
- 18 Sept 26 −15
- Malware scan: pass → unverified ▼ security
- 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.
- 16 Sept 26 +15
- Malware scan: unverified → pass ▲ security
- 15 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.
- 14 Sept 26 −15
- Malware scan: pass → unverified ▼ security
- 13 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 80 to 83. That category is still filling its 30-day observation window: 24 days of observed history at the previous scan, 25 at this one. The score rises as the window fills, whether or not the server changes.
- 12 Sept 26 −3
- 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/junai-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 15 packages
| Packages resolved | 15 |
|---|---|
| Stale | 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 →
get_pipeline_status Get Pipeline Status ~21
Return current pipeline status and best-effort next transition summary.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
notify_orchestrator Notify Orchestrator ~52
Record stage completion and ask pipeline-runner for deterministic next transition.
| Name | Type | Req | Description |
|---|---|---|---|
| artefact_path | – | – | – |
| result_payload | – | – | – |
| result_status | string | yes | – |
| stage_completed | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
pipeline_init Pipeline Init ~126
Initialise a new pipeline state file from the template. Requires confirm=True to proceed — this prevents accidental invocation mid-run. Use when starting a brand-new feature or hotfix pipeline. If a pipeline-state.json already exists, it will be overwritten. _bypass_active_check is an internal flag used by pipeline_reset to skip the active-pipeline guard. Do not set this from user-facing calls.
| Name | Type | Req | Description |
|---|---|---|---|
| _bypass_active_check | boolean | – | – |
| confirm | boolean | – | – |
| feature | string | yes | – |
| project | string | yes | – |
| type | string | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
pipeline_reset Pipeline Reset ~99
Reset the current pipeline state and start a new pipeline run. Identical to pipeline_init but semantically signals resetting an existing pipeline rather than creating a fresh one. Requires confirm=True. Use when a pipeline has closed and the user wants to start the next feature, or when explicitly restarting a failed/stale pipeline.
| Name | Type | Req | Description |
|---|---|---|---|
| confirm | boolean | – | – |
| feature | string | yes | – |
| project | string | yes | – |
| type | string | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
run_command Run Command ~183
Execute a shell command in the workspace root and return stdout, stderr, exit code. Use this for running tests (pytest, playwright), linters (black, ruff), formatters, build steps, or any other shell command the pipeline needs to execute hands-free. Agents should prefer this over asking the user to run commands manually in a terminal.
| Name | Type | Req | Description |
|---|---|---|---|
| command | string | yes | Shell command to run (e.g. ".venv/Scripts/pytest tests/ -v"). Executed in the workspace root directory with shell=True. |
| max_output_chars | integer | – | Truncate combined output to this many characters to avoid flooding the context window. Default 20000. |
| timeout | integer | – | Seconds before the process is killed. Default 60s. Increase for long test suites, Playwright runs, or slow build steps. |
Structured output declared, but exposes no named fields.
No examples provided.
satisfy_gate Satisfy Gate ~25
Set a supervision gate to satisfied (true).
| Name | Type | Req | Description |
|---|---|---|---|
| gate_name | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
set_pipeline_mode Set Pipeline Mode ~29
Set the pipeline mode to supervised, assisted, or autopilot.
| Name | Type | Req | Description |
|---|---|---|---|
| mode | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
validate_deferred_paths Validate Deferred Paths ~30
Validate deferred item file paths and attempt path correction where possible.
| Name | Type | Req | Description |
|---|---|---|---|
| deferred_items | array | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
What is the junai Pipeline MCP server?
junai Pipeline MCP is listed in the public MCP registry as io.github.saajunaid/junai-mcp. Agentic pipeline orchestration MCP server for AI-driven development workflows. This page covers its PyPI package (junai-mcp).
Is the junai Pipeline MCP server safe to use?
junai Pipeline MCP scores 55 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 junai Pipeline MCP server expose?
junai Pipeline MCP exposes 8 tools: notify_orchestrator, validate_deferred_paths, get_pipeline_status, set_pipeline_mode, satisfy_gate, and 3 more. Their descriptions and schemas cost roughly 565 tokens of context every time the server is loaded.
Is the junai Pipeline MCP server still maintained?
junai Pipeline 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.