Bring Dora Metrics
to LlamaIndex
Learn how to connect LinearB to LlamaIndex and start using 7 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for Subscribers
What is the LinearB MCP Server?
Connect your LinearB account to any AI agent to automate your engineering intelligence and DORA metrics reporting. This MCP server enables your agent to query cycle time, track deployments, and report incidents directly from natural language interfaces.
What you can do
- Metric Ingestion — Query complex engineering metrics including cycle time, coding time, and pickup time across teams
- Deployment Management — Inform LinearB of new software releases by reporting Git refs (SHAs or tags) programmatically
- Incident Tracking — Report and list engineering incidents to maintain accurate Change Failure Rate and MTTR metrics
- Metadata Oversight — List teams and connected repositories to map technical IDs to organizational structures
- DORA Analytics — Retrieve aggregated performance data to identify bottlenecks in your delivery pipeline
How it works
1. Subscribe to this server
2. Enter your LinearB Public API Key
3. Start managing your engineering metrics from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Engineering Managers — Monitor team cycle times and delivery health via simple natural language commands
- DevOps Engineers — Automate the reporting of deployments and incidents directly from CI/CD pipelines or IDEs
- CTOs — Quickly audit organizational performance and DORA metrics without opening the dashboard
Built-in capabilities (7)
List all connected repositories
List all teams defined in LinearB
List recent deployments
List engineering incidents
Requires a JSON body with requested_metrics and time_ranges. Query software engineering metrics (v2)
Requires repo_id and ref. Report a new deployment to LinearB
Requires provider_id and started_at. Report a new incident
Why LlamaIndex?
LlamaIndex agents combine LinearB tool responses with indexed documents for comprehensive, grounded answers. Connect 7 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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Data-first architecture: LlamaIndex agents combine LinearB tool responses with indexed documents for comprehensive, grounded answers
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Query pipeline framework lets you chain LinearB tool calls with transformations, filters, and re-rankers in a typed pipeline
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Multi-source reasoning: agents can query LinearB, a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what LinearB tools were called, what data was returned, and how it influenced the final answer
LinearB in LlamaIndex
LinearB and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect LinearB to LlamaIndex through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for LinearB in LlamaIndex
The LinearB MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 7 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LlamaIndex only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
LinearB for LlamaIndex
Every tool call from LlamaIndex to the LinearB MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I query cycle time for a specific team?
Use the query_software_metrics tool and include the team name or ID in the group_by parameter of your JSON query.
What is the difference between coding_time and pickup_time?
Coding time is the duration from the first commit to the PR creation. Pickup time is the duration from the PR creation to the first review activity.
Can I report a release from the agent?
Absolutely. Use the record_new_deployment tool with the Git SHA or tag and the repository ID to inform LinearB that a deployment has occurred.
How does LlamaIndex connect to MCP servers?
Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
Can I combine MCP tools with vector stores?
Yes. LlamaIndex agents can query LinearB tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
Does LlamaIndex support async MCP calls?
Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.
BasicMCPClient not found
Install: pip install llama-index-tools-mcp