Solutions | Agent effectiveness

Higher accuracy. Faster execution. Fewer tokens.

Most agent failures are context failures. Sourcegraph MCP gives coding agents the right context across massive codebases at the right time, delivering higher accuracy, 38% faster execution, and 30% token savings.

Higher accuracy, faster execution, fewer tokens

Trusted by the world's largest dev teams

The proof

Benchmarked on real, large-scale codebases

CodeScaleBench evaluates coding agents across 370 tasks spanning 40+ open-source repositories and 9 languages, comparing the same agent with and without Sourcegraph MCP retrieval tools. Read the full report →

0.140 → 0.478

Precision@5 with Sourcegraph MCP vs. a local grep/file baseline (CodeScaleBench, 370 tasks)

0.099 → 0.262

F1@5 with Sourcegraph MCP vs. a local grep/file baseline (CodeScaleBench, 370 tasks)

2 hrs → 89 sec

Time to complete a real Kubernetes cross-file task, baseline vs. Sourcegraph MCP

Code Finder

Faster, cheaper file discovery for agents

On a benchmark of file-finding tasks across repositories from small to very large, Code Finder reached comparable result quality while finishing faster and costing less than a coding agent doing the search itself. Read the benchmark →

Time

Code Finder 1.00×
Coding agent, MCP tools 1.14×
Coding agent, local search 2.19×

Cost

Code Finder 1.00×
Coding agent, MCP tools 1.63×
Coding agent, local search 1.32×
Relative to Code Finder. Lower is better.
The context problem

Most agent failures are context failures, not model failures

When an agent can't see across repositories, it improvises: hallucinating file paths, missing dependencies, and shipping incomplete fixes with total confidence. Sourcegraph MCP gives agents precise, cross-repository code intelligence, so they retrieve real answers instead of guessing them. See how Sourcegraph MCP works →

Same prompt. Two agents. Real queries run against public open-source repos.
Agent
Agent Sourcegraph MCP
keyword_search({ query: "three-way merge" })
keyword_search({ query: "Settings Sync merge conflicts" })
keyword_search({ query: "added removed updated conflicts" })
read_file({ path: "...common/settingsMerge.ts" })
See it in action

Watch the difference context makes

One prompt, two agents: one with only local file access, one with Sourcegraph MCP. Only one of them finds everything. See the full comparison →

Coding AgentAgent
Read models/user.go

I'll add a Role field to the User struct and update the store methods.|

Edit models/user.go — added Role string field
Edit database/user_store.go — updated Create/Update

Done! I've added:

  • Role field to the User struct
  • Updated Create and Update to persist the role
  • Added a GetByRole query method
You'll want to add a migration for the new column and update your auth checks.
What the agent missed
Auth middleware — no role check, any user can access admin routes
API response DTO — role never returned to clients
Audit logging — role changes not tracked, no compliance trail
/admin frontend routes — no guard, UI still accessible to all
Invite flow — new users created without a default role
4 integration tests — assert on user shape, will break
Coding AgentAgent + Sourcegraph MCP sg mcp
sg_keyword_search "User struct" across 2,847 repositories
Found 31 files referencing User across 7 layers
models/user.go
middleware/auth.go
api/dto/user_response.go
routes/admin/guard.ts
+27 more files

This is a cross-cutting change. Here's my plan:|

Plan 8 steps
Edit 12 files across 7 layers

Complete. All layers updated, tests passing. Full diff ready for review.|

Nothing missed
Auth middleware API response DTO Audit logging Frontend routes Invite flow Integration tests

How teams use Sourcegraph to make agents effective

Debugging and incident response

Agents trace an incident across every affected repository, following real dependencies and commit history instead of guessing at root cause.

Cross-repo refactors and migrations

Agents can follow API and library dependencies across repos, so proposed changes land correctly on the first try.

Onboarding and codebase navigation

New agents get instant, accurate answers to "where is X and how does it work" instead of stale docs and outdated assumptions.

Give your agents the context to succeed

See how Sourcegraph MCP and Deep Search help your team's AI coding agents deliver correct, complete changes across your entire codebase.